#data science courses in toronto

[suhasini123]

An artificial intelligence (AI) course is an educational program or training that focuses on teaching individuals the principles, techniques, and applications of artificial intelligence. Datamites is an organization that offers various courses and training programs in the field of data science, artificial intelligence, and machine learning.

[tahacollege]

What is the best college that offers certificate programmes in Toronto?

Are you looking for a career in beauty, business, or health? Do you want to learn from the best instructors and gain hands-on experience in your field of interest? If yes, then you should consider enrolling in one of the certificate programs in Toronto offered by Taha College.

Taha College is a leading educational institution that provides various certificate programs in beauty, business, and health. These programs are designed to equip you with the skills and knowledge you need to succeed in your chosen profession. Whether you want to become a medical aesthetician, a personal support worker, an international business administrator, or a medical office administrator, Taha College has a program for you.

Some of the certificate programs offered by TAHA College are:

Medical Aesthetics Certificate: This program teaches you how to perform various cosmetic procedures, such as facials, manicures, pedicures, waxing, threading, body care, hair styling, and makeup application. You will also learn about skin care products, anatomy and physiology, infection control, and client consultation. This certificate programs in Toronto prepares you for a rewarding career as a medical aesthetician in spas, salons, clinics, or your own business.

Personal Support Worker Certificate: This program trains you to provide personal care and assistance to clients who need support due to ageing, illness, injury, or disability. You will learn how to perform tasks such as bathing, dressing, feeding, transferring, and administering medication. You will also learn about communication skills, safety procedures, and ethical issues. This certificate programs in Toronto prepares you for a fulfilling career as a personal support worker in hospitals, long-term care facilities, home care agencies, or private residences.

International Business Administration Certificate: This program educates you on the fundamentals of international trade and marketing. You will learn how to conduct business transactions across borders, manage finances and budgets, solve problems and make decisions, and work effectively in teams. You will also learn about cultural diversity, legal aspects, and global trends. This certificate programs in Toronto prepares you for an exciting career as an international business administrator in various sectors and industries.

Medical Office Administration Certificate: This program instructs you on how to perform administrative duties in a health care setting. You will learn how to use medical terminology, software applications, and office equipment. You will also learn how to schedule appointments, process insurance claims, maintain records, and communicate with patients and health care professionals. This program prepares you for a vital role as a medical office administrator in hospitals, clinics, laboratories, or other health care facilities.

These are just some of the certificate programs in Toronto offered by Taha College. All of these programs are taught by qualified and experienced instructors who will guide you through the theoretical and practical aspects of your chosen field. You will also have the opportunity to participate in field placements where you can apply your skills and knowledge in real-world situations.

If you are interested in enrolling in one of these certificate programs in Toronto or want to know more about them, please visit the TahaCollege website

[ok-orange-8774]

Data science is a field of study that works with enormous amounts of data utilizing contemporary technologies and methodologies to uncover hidden patterns, obtain valuable information, and make business decisions. Datamites provides online data science training in Toronto.

[xenosagaepisodeone]

the thing is though that these checklists don’t mean if you have BPD it is not allowed that you have nightmares / if you have CPTSD you are legally obligated to never experience impulsiveness etc etc; it’s not just “making stuff up” — though ig in the strictest sense yeah, first you make stuff up but then you test it and see if your hypotheses align with the population. Basically chances are if you meet 8/9 BPD criteria and some for CPTSD but not enough to meet the diagnostic standard (which afaik isn’t recognized just yet but i think they’re trying to get it recognized in the diagnostic manuals but correct me if i’m wrong) then it’s pretty likely you’re going to respond better to BPD treatment and ALSO if your practitioner completely ignores one diagnosis in favor of the other they’re probably not that good at their job. Psychology doesn’t speak in “rules” and absolutes, it speaks in trends and likelihoods and everyone trying to sell you a 100% true and immovable psychology fact is a sham

as someone who unfortunately has a degree in psychology (and whose undergrad began right as the infamous replication crisis became more widely acknowledged in the field), yes, historically a lot of this field is bias and hegemony imbued with some metric. when homosexuality was still classified as a mental disorder, the conversion therapy program by masters and johnson (who were like, some of the earliest pioneers of research into human sexual responses lmao) would often boast high success rates due to participants merely adopting signifiers of heterosexuality. the modern day pop psychology movement (and it's subfields, new ageism, self help books, uhhh Market Christianity) also cannot be disentangled from academic psychology, which further bends the way in which people understand and interact with psychological phenomena. this of course does not mean that all data is junk data, or that methods of measurement are without some rigor, or that therapy is completely useless, but it's just patently incorrect to insist that this field is even predominantly an apolitical force attempting to further our understanding of human beings. it's bizarre that you acknowledge that credentialized individuals in the field can be flawed while also being uncritical of psychological categorization for mental illness.

It's not that I don't get what you're saying, but it's not reflective of reality. yes, I know that practitioners are supposed to help you feel out your symptoms and see what treatment works for you, but that isn't just what they're doing (assuming it's even being done with care and competence). it's inaccurate to insist that psychology doesn't speak in absolutes- I know that we are taught not to do this, but for any social science related field this is the equivalent of going "stop hitting yourself". in any practical real-world setting where accredited institutional psychology is present, there are rules. in a clinical setting, there are rules, and you can be inpatiented against your will for breaking those rules (or recently here in canada, randomly stripped of your driver's license). in neuromarketing (<- yes this is a real discipline.), which is intensively oriented towards results due to the profit incentive, there are rules. the conditions of release for many offenders necessitates staying on court-mandated medication or participating in specific programs. when H.B. Phrenology from The Heritage Foundation wheels out his thousandth manicured study on crime and race (and when a different journal publishes a study indirectly debunking it), that is him tacitly acknowledging that there are rules.

anyway did I ever tell you guys that in my first year at University of Toronto (UTSC campus baybee) they brought in a guest speaker to my abnormal psych course who gave us a lengthy talk on how autogynephilia theory is objectively true. this was like 2013ish maybe 2014 btw.

[umichenginabroad]

Week 0: Arrival in Berlin

Hello my name is Dervin and I will be documenting my journey on this blog for you guys to enjoy. To briefly introduce myself, I am a rising Sophomore currently studying Data Science in the College of Engineering and for the next 6-7 weeks or so, I will be studying Robotics Programming at the Technische Universität of Berlin (TUB). 

Of course you guys are just dying to know about my journey here. Well, the flight to Berlin was broken into two legs. The first leg, a 7 hour flight from Toronto (which I had to drive 4 hours to get to) to Frankfurt, went pretty smoothly as even though I was cursed with the middle seat, the power of Christopher Nolan movies pushed me through the flight, despite having not slept for the entire flight. In the second leg however, a 45 minute flight from Frankfurt to Berlin, that lack of sleep shortly caught up to me as shortly after take off, I fell asleep and didn’t wake up until after people started gathering their belongings to exit the plane in Berlin. At the airport, I met up with all the other students who had landed in Berlin and we were on our way off to our apartments via the U-Bahn. Shortly after arriving, some of my fellow friends and I went out to shop for essential goods as well as find a place to eat.

My 4 years of learning German was also tested today. As I haven't actually practiced German since high school, I thought that I had lost a lot of it. However, upon my arrival today, I was surprised to see that I hadn’t actually forgotten that much since high school. I was still able to read basic signs and sentences, and still had enough conversational skills to order small meals and buy groceries in German. As I stay longer in Germany, I hope to see my German get better over time and gain more confidence when speaking.

Emotionally speaking, I'm mixed. While I am excited to start classes and get to immerse myself in the city, I am also nervous about how different life will be here in Europe. I am nervous about the prospect of screwing up, making a fool of myself in a country where the culture is foreign to me. However, after watching Interstellar and Inception on the plane, I realized that these feelings are natural and sometimes all it takes to conquer them is just a leap of faith, so that’s what I’m gonna do. I’m gonna take that leap of faith and I'll take you guys along to see what's on the other side.

Dervin Tian

Data Science

Engineering Laboratory Experience at TUB in Berlin, Germany

[insanityclause]

I think Tucker is nuts, and no, the US is not going to invade Canada, but I know a lot of ex Canadians, and none are going back. A lot of what that person posted about their country is not true, but look at the population of both countries. Of course there is more crime in the US, but better education? Hardly. I do know they are more lenient about who they let in because my extended Iranian family couldn’t get in the US, so they had to go to Canada.

Hi. Canadian here. @doctortwhohiddles' country IS my country, so I know exactly what of that post is true. Pretty much every single word.

Greater life expectancy? True. (In part due to universal health care and gun control.)

And since Tucker was using last year's hostage taking 'Freedom Convoy' for the basis of his talking points, let's look at this data:

Crime??

Education?

PISA scores for Reading, Math & Science (2018)

Costs for post-secondary are far lower here, too, and funding is pretty good.

University of Toronto - $4700 USD/year (non-Ontario resident)

McGill - $6500 USD/year (non-Quebec resident)

University of British Columbia - $4200 USD/year

Comparable universities in the US:

Johns Hopkins - $60,000/yr

University of Michigan - $52,000/yr ($26,000 if you're a resident)

Northwestern - $60,000/yr

UK universities just for fun:

$11,000 USD/yr

And the public elementary/secondary system is excellent, compared to what you get in publicly funded education in the US or UK. The 'posh public school' argument literally does not exist here. No one cares where you went to high school.

Plus, safe schools. We have had 8 school shootings since 1975. Total. Including universities. Last one was 2016. The US had ~500 in the same time frame, and 57 in 2019 alone. Even accounting for the population difference, you're on the losing side in that one.

Not sure why our immigration system is your concern; it's worked really well for us. A mosaic rather than a melting pot.

[religion-is-a-mental-illness]

By: Cory Clark and Bo Winegard

Published: Jul 27, 2020

Women who seek to be equal with men lack ambition. ~Timothy Leary

Many feminists and progressives argue that the West is plagued by pervasive misogyny. In fact, this claim is made with such frequency, and is so rarely challenged, that it has become part of the Left’s catechism of victimhood, repeated by rote without a second thought. The only real question is how powerful and pernicious the misogyny is. Real-world data, however, suggest a different narrative, complicated by the fact that men have worse outcomes in many domains. For example, they are much more likely to be incarcerated, to be shot by the police, to be a victim of violent crime, to be homeless, to commit suicide, and to die on the job or in combat than women. Furthermore, they have a shorter life expectancy and are less likely to be college educated than women. Although these (and similar) data can be reconciled with the pervasive misogyny theory, they should at least give pause to the open-minded. The best data from contemporary social science tell a rather different story and suggest that the very persistence of the pervasive misogyny narrative is itself a manifestation of the opposite: society is largely biased in favor of women.

The world, of course, is a messy place and disparities between men and women may have many causes. This is why carefully controlled social science is useful for examining the extent, direction, and nature of sex-related biases. Although the details can get complicated, the basic idea behind most bias studies is pretty straightforward. Researchers present participants with identical information that has some bearing on the abilities of males or females while manipulating which sex the information is about. For example, they might ask two groups of people to evaluate identical essays, telling one group that it was written by a man and the other group that it was written by a woman. If participants who believed the essay was written by a man evaluated it as more compelling, more intelligent, more insightful, and so on than participants who believed it was written by a woman, psychologists would consider that a bias in favor of men. Similarly, if one asked two groups of people to evaluate identical scientific studies that discovered that either men or women performed better on a measure of leadership, and participants who read that men outperformed women regarded the study as higher quality than participants who read that women outperformed men, psychologists would consider this a male-favoring bias (everyday people consider such patterns to be biases as well).

Contrary to expectations from the pervasive misogyny theory, across a variety of topics, samples, and research teams, recent findings in psychology suggest that such biases often favor women. For example, a paper just published in the British Journal of Psychology led by Steve Stewart-Williams found that people respond to research on sex differences in ways that favor females. In two studies, participants were asked to read a popular science article that was experimentally manipulated to suggest that either men or women have a more desirable quality (for example, men/women are better at drawing or men/women lie less often). Participants evaluated the female-favoring research more favorably than the male-favoring research. Specifically, participants found the female-favoring research more important, more plausible, and more well-conducted and found the male-favoring research more offensive, more harmful, more upsetting, and more inherently sexist. This pro-female bias was observed among both male and female participants, and in study two, the researchers replicated the results in a south-east Asian sample.

In some of our own work, we found a similar pattern for the socially desired trait of intelligence. In two studies, participants read about a (fictitious) scientific study that identified a gene associated with higher intelligence that purported to explain why either (1) men score higher on intelligence tests than women, (2) women score higher on intelligence tests than men, or (3) men and women score roughly equally on intelligence tests. Participants evaluated the scientific study to be similarly credible when it drew the conclusion that men and women score equally on intelligence tests and when women were said to score higher than men, but participants found the study less credible when it suggested that men score higher on intelligence tests than women.

In a related study, participants read about a college entrance exam that is remarkably accurate at predicting academic performance in college. They were told that either men tend to outperform women or that women tend to outperform men on the exam. Participants endorsed use of the exam more when women were said to outperform men than when men were said to outperform women. These findings suggest that people more readily accept the notion that women could be smarter than men than vice versa.

Scholars observed a similar pattern among psychology academics. In 2017, the social scientists William von Hippel and David Buss emailed a survey to a sample of psychologists, asking their beliefs about a variety of evolutionary claims and findings. These psychologists were more likely to endorse a female-favoring sex difference than a male-favoring one. Specifically, they were more likely to accept that women could have evolved to be more verbally talented than men than that men could have evolved to be more mathematically talented than women. Although these sex differences are not perfectly symmetrical (one regards verbal ability and the other mathematical ability), there is little reason to believe that an evolutionary explanation for one sex difference is more plausible than the other. Like non-academics, scientists themselves may have preferences for pro-female information over pro-male information.

We have also found that people have a stronger desire to censor science that disfavors women. In this study, participants were asked to read a series of passages from books and to decide whether the text should be censored (for example, whether it should be removed from the library, whether a professor should not be allowed to require it for class). One passage argued that either men or women make better leaders. The results showed that people wanted to censor the book more when it argued that men make better leaders than women than when it argued the opposite.

Ironically, these pro-female preferences may explain why mainstream narratives focus so assiduously on the possibility of anti-female biases: society cares more about the wellbeing of women than men and is thus less tolerant of disparities that disfavor them. A series of studies led by Katharina Block found that people care more about female underrepresentation in careers than male underrepresentation. In one such study, for example, participants were told that a particular career was dominated either by men or women. Participants were then asked whether policies and programs should be put in place to encourage whichever group was underrepresented to enter that career and whether efforts should be made to actively recruit the underrepresented group. Participants were more likely to support this social action when women were underrepresented than when men were.

Moreover, when the career was said to be accompanied by a high salary, people were more likely to say that prohibitive norms were blocking women from entering the male-dominated career than that prohibitive norms were blocking men from entering the female-dominated fields. So, people are more likely to believe that external barriers explain women’s underrepresentation in desirable careers than men’s underrepresentation. These findings suggest that when real world disparities exist between men and women, people are more likely to care and more likely to try to engage in corrective behavior when women are at a disadvantage.

One explanation for these pro-female biases is that humans may have evolved a general protectiveness of women. Indeed, numerous reports over the past few decades have shown that people have more sympathy for female than male suffering. For just a few examples, people are less willing to harm a female than a male, women receive more help than men, those who harm women are punished more severely than those who harm men, and women are punished less severely than men for the same crimes.

Such findings contradict the concept of “himpathy,” introduced in philosopher Kate Manne’s successful book Down Girl: The Logic of Misogyny. Anecdotes can create an illusion of excessive sympathy for men, but more systematic analyses suggest the opposite: People are vastly more sympathetic toward women. The success of Manne’s book might indeed be a manifestation of these very sympathies, because people are more alarmed and disturbed by the possibility of a bias against women than against men.

Concerns about women’s wellbeing are so strong that researchers often frame pro-female preferences and biases as harmful to women. For example, in a series of studies led by Lily Jampol, researchers asked participants to evaluate essays and give feedback to the author. Participants who then discovered the essay writer was female were more likely to adjust their performance evaluations upward than participants who were told the essay writer was male. This paper was entitled “The Dark Side of White Lies in the Workplace: Feedback to Women Is Upwardly Distorted,” highlighting the potentially harmful consequences of providing softened or distorted feedback to women.

Of course, it is possible that overly positive feedback harms women in the long-run, but it might also help them, for example, if it boosts their confidence, or if evaluators internalize the flattering feedback. Furthermore, it’s difficult to imagine that similar but opposite results would be framed as potentially deleterious to men. It seems as if research is often framed as “if biases favor men, then that’s bad for women; if biases favor women, then that’s also bad for women.” For example, the women-are-wonderful effect, which is the tendency for people to view women more favorably than men, is often regarded as a form of benevolent sexism against women. We eagerly await a paper that claims preferences for men as teachers or leaders illustrates a kind of benevolent sexism against men.

Though not exhaustive, the table below summarizes findings from numerous studies demonstrating biases and attitudes that appear to favor women.

Various findings demonstrating biases, attitudes, and treatments that favor women over men

People prefer to spare the lives of females over the lives of males : Awad, Bonnefon, Shariff, & Rahwan, 2019

People support more social action to correct female underrepresentation in careers than male underrepresentation : Block, Croft, De Souza, & Schmader, 2019

Both male and female faculty preferred hiring a female over a male applicant for tenure-track assistant professorships in STEM : Ceci & Williams, 2015

Offenders who victimize females receive longer sentences than those who victimize males; males who victimize females receive the longest sentences : Curry, Lee, & Rodriguez, 2004

Police respond more negatively toward hypothetical male rape victims than hypothetical female rape victims : Davies, Smith, & Rogers, 2009

Women receive more help than men : Eagly & Crowley, 1986

Women are evaluated more favorably than men : Eagly, Mladinic, & Otto, 1991

People are less willing to harm females than males : FeldmanHall, Dalgleish, Evans, Navrady, Tedeschi, & Mobbs, 2016

In vehicular homicides, drivers who kill women are given longer sentences than those who kill men : Glaeser & Sacerdote, 2003

People are particularly intolerant of aggression from a male and aggression directed toward a female : Harris & Knight-Bohnhoff, 1996

People adjust essay performance evaluations upward when they learn the writer is female : Jampol & Zayas, 2017

Women are punished less than men for the same crime : Mazzella & Feingold, 1994

Controlling for numerous characteristics, men receive longer prison sentences than women : Mustard, 2001

People have more empathy for female than male perpetrators and female than male victims : Osman, 2011

Women are more easily seen as victims and men as perpetrators : Reynolds, Howard, Sjåstad, Zhu, Okimoto, Baumeister, Aquino, & Kim, 2020

People attribute less guilt to a female-on-male sexual aggressor than a male-on-female sexual aggressor : Russel, Oswald, & Kraus, 2011

People have less sympathy for male than female perpetrators and more sympathy for female than male victims : Savage, Scarduzio, Lockwood Harris, Carlyle, & Sheff, 2017

Female sex offenders are given shorter sentences than male sex offenders : Shields & Cochran, 2019

Women’s aggression is perceived as more acceptable than men’s aggression : Stewart-Williams, 2002

People evaluate science on female-favoring sex differences more favorably than science on male-favoring sex differences : Stewart-Williams, Chang, Wong, Blackburn, & Thomas, 2020

Psychologists agree more that it is possible that women evolved to be more verbally talented than men than that men evolved to be more mathematically talented than women : von Hippel & Buss, 2017

People evaluate science that suggests that women score higher on IQ tests than men more favorably than science that suggests the opposite : Winegard, Clark, Hasty, & Baumeister, 2018

People wish to censor a book that suggests that men evolved to be better leaders than women more than a book that suggests the opposite : Winegard, Clark, Bunnel, & Farkas, 2019

As noted above, an important feature of many of these studies (though not all of them) is that they are experimental—they randomly assign participants to evaluate information with some bearing on outcomes for men or women (or a man or woman). Many scholars who argue that sexism against women is still a major problem in modern Western societies point to real-world disparities between men and women (but ignore many others). For example, they point out that women are underrepresented in high-paying STEM careers and leadership positions, and full-time working women earn less than full-time working men. However, the existence of such differences tells us little about the causes of them, for just as correlation does not equal causation, so too disparity does not equal discrimination. And, in fact, the claim that women are underrepresented in STEM because qualified male job candidates are preferred over equally qualified female job candidates no longer seems plausible. Experimental work suggests that faculty in STEM fields have demonstrated a preference for female applicants over equally qualified male applicants. Other explanations, such as differences in personality and vocational interests therefore appear much more promising.

This does not mean, of course, that there are no biases against women. For a long time, women in the West were treated as property and were considered emotional, irrational, and incapable of contributing significantly to higher culture. It is not unimaginable that some of these prejudices still persist and shape society. For just one example, there seems to be a sort of genius bias against women, such that people more readily associate men with extremely high levels of intelligence than women. And although there is reason to believe that men might be more highly represented at the highest (and lowest) ends of intelligence, this stereotype could explain part of the underrepresentation of women at the highest ends of achievement. However, overall, the results presented here make the claim that the West is pervaded by misogyny difficult to maintain.

The mainstream view is that we live in a sexist patriarchy that is persistently unfair toward women and privileges men in nearly all ways. And any claims to the contrary are treated as the protestations of benighted conservatives or other masculinist cranks. A Google Scholar search for misogyny yielded 114,000 results, whereas a search for misandry yielded only 2,340. We suspect this difference in interest in misogyny over misandry reflects not the relative prevalence of each type of prejudice, but rather greater concern for the wellbeing of women than men. All of the arguments, anecdotes, and data forwarded to support the narrative that we live in an implacably misogynistic society, in fact, may be evidence of precisely the opposite.

[ Archive: https://archive.is/gpp2b ]

[jcmarchi]

AI Algorithm Improves Predictive Models of Complex Dynamical Systems - Technology Org

New Post has been published on https://thedigitalinsider.com/ai-algorithm-improves-predictive-models-of-complex-dynamical-systems-technology-org/

AI Algorithm Improves Predictive Models of Complex Dynamical Systems - Technology Org

Researchers at the University of Toronto have made a significant step towards enabling reliable predictions of complex dynamical systems when there are many uncertainties in the available data or missing information.

Artificial intelligence – artistic concept. Image credit: geralt via Pixabay, free license

In a recent paper published in Nature, Prasanth B. Nair, a professor at the U of T Institute of Aerospace Studies (UTIAS) in the Faculty of Applied Science & Engineering, and UTIAS PhD candidate Kevin Course introduced a new machine learning algorithm that surmounts the real-world challenge of imperfect knowledge about system dynamics.

The computer-based mathematical modelling approach is used for problem solving and better decision making in complex systems, where many components interact with each other.  

The researchers say the work could have numerous applications ranging from predicting the performance of aircraft engines to forecasting changes in global climate or the spread of viruses.  

From left to right: Professor Prasanth Nair and PhD student Kevin Course are the authors of a new paper in Nature that introduces a new machine learning algorithm that addresses the challenge of imperfect knowledge about system dynamics. Image credit: University of Toronto

“For the first time, we are able to apply state estimation to problems where we don’t know the governing equations, or the governing equations have a lot of missing terms,” says Course, who is the paper’s first author.   

“In contrast to standard techniques, which usually require a state estimate to infer the governing equations and vice-versa, our method learns the missing terms in the mathematical model and a state estimate simultaneously.”  

State estimation, also known as data assimilation, refers to the process of combining observational data with computer models to estimate the current state of a system. Traditionally, it requires strong assumptions about the type of uncertainties that exist in a mathematical model.   

“For example, let’s say you have constructed a computer model that predicts the weather and at the same time, you have access to real-time data from weather stations providing actual temperature readings,” says Nair. “Due to the model’s inherent limitations and simplifications – which is often unavoidable when dealing with complex real-world systems – the model predictions may not match the actual observed temperature you are seeing.  

“State estimation combines the model’s prediction with the actual observations to provide a corrected or better-calibrated estimate of the current temperature. It effectively assimilates the data into the model to correct its state.”  

However, it has been previously difficult to estimate the underlying state of complex dynamical systems in situations where the governing equations are completely or partially unknown. The new algorithm provides a rigorous statistical framework to address this long-standing problem.  

“This problem is akin to deciphering the ‘laws’ that a system obeys without having explicit knowledge about them,” says Nair, whose research group is developing algorithms for mathematical modelling of systems and phenomena that are encountered in various areas of engineering and science.  

A byproduct of Course and Nair’s algorithm is that it also helps to characterize missing terms or even the entirety of the governing equations, which determine how the values of unknown variables change when one or more of the known variables change.   

The main innovation underpinning the work is a reparametrization trick for stochastic variational inference with Markov Gaussian processes that enables an approximate Bayesian approach to solve such problems. This new development allows researchers to deduce the equations that govern the dynamics of complex systems and arrive at a state estimate using indirect and “noisy” measurements.  

“Our approach is computationally attractive since it leverages stochastic – that is randomly determined – approximations that can be efficiently computed in parallel and, in addition, it does not rely on computationally expensive forward solvers in training,” says Course.   

While Course and Nair approached their research from a theoretical viewpoint, they were able to demonstrate practical impact by applying their algorithm to problems ranging from modelling fluid flow to predicting the motion of black holes.   

“Our work is relevant to several branches of sciences, engineering and finance as researchers from these fields often interact with systems where first-principles models are difficult to construct or existing models are insufficient to explain system behaviour,” says Nair.  

“We believe this work will open the door for practitioners in these fields to better intuit the systems they study,” adds Course. “Even in situations where high-fidelity mathematical models are available, this work can be used for probabilistic model calibration and to discover missing physics in existing models.   

“We have also been able to successfully use our approach to efficiently train neural stochastic differential equations, which is a type of machine learning model that has shown promising performance for time-series datasets.”    

While the paper primarily addresses challenges in state estimation and governing equation discovery, the researchers say it provides a general groundwork for robust data-driven techniques in computational science and engineering.  

“As an example, our research group is currently using this framework to construct probabilistic reduced-order models of complex systems. We hope to expedite decision-making processes integral to the optimal design, operation and control of real-world systems,” says Nair.   

“Additionally, we are also studying how the inference methods stemming from our research may offer deeper statistical insights into stochastic differential equation-based generative models that are now widely used in many artificial intelligence applications.” 

Source: University of Toronto

You can offer your link to a page which is relevant to the topic of this post.

[pratiksha-more]

Exploring Computer Science Programs in Canada: A Guide for Indian Students

Canada has become a preferred destination for Indian students seeking advanced education in technology and computer science. As one of the top courses in Canada, computer science offers vast opportunities for growth in areas like artificial intelligence, data science, cybersecurity, and software development. With its world-renowned universities, thriving tech industry, and favorable immigration policies, Canada stands out as an ideal destination for Indian students aspiring to build successful careers in technology. If you're planning to pursue computer science in Canada, consulting with an overseas education consultancy can help streamline your journey by offering expert guidance on university selection, visa processes, and scholarships.

Why Study Computer Science in Canada?

Canada’s reputation for academic excellence is well-deserved, particularly in the fields of technology and innovation. Computer science programs in Canadian universities are designed to provide a strong theoretical foundation while emphasizing practical skills through internships, co-op programs, and industry collaborations.

Here are a few reasons why Indian students should consider studying computer science in Canada:

Global Recognition: Canadian degrees are recognized worldwide, and universities are consistently ranked among the top institutions for computer science.

Thriving Tech Industry: Cities like Toronto, Vancouver, and Montreal are tech hubs, home to global tech giants such as Google, Microsoft, and Amazon. These companies offer excellent internship and job opportunities for computer science graduates.

Research Opportunities: Canadian universities place a strong emphasis on research, providing Indian students the chance to work on cutting-edge projects in areas like machine learning, quantum computing, and AI.

Pathway to Permanent Residency: Canada’s immigration policies are student-friendly, and graduates from Canadian universities are eligible for post-graduation work permits and have a clear path to permanent residency.

Top Canadian Universities for Computer Science

Indian students have a wide range of choices when it comes to selecting a university for computer science. Some of the top institutions offering computer science programs in Canada include:

University of Toronto: Consistently ranked as one of the best universities for computer science, the University of Toronto offers diverse specializations such as AI, data science, and computational biology. It is known for its strong research focus and industry collaborations.

University of British Columbia (UBC): UBC’s computer science program is highly regarded for its innovative curriculum and opportunities for interdisciplinary learning. The university offers a wide range of research opportunities and is located in the heart of Vancouver, a major tech hub.

McGill University: Located in Montreal, McGill University is renowned for its computer science program, offering courses in areas like AI, software engineering, and computational theory. McGill’s emphasis on research and practical training prepares students for successful careers in both academia and industry.

University of Waterloo: Waterloo is known for its co-op program, allowing students to gain valuable work experience while studying. The university has a strong focus on innovation and entrepreneurship, with many students going on to work in top tech companies globally.

Simon Fraser University: Situated in Vancouver, Simon Fraser University is well-regarded for its computer science programs, with a particular focus on AI, data mining, and robotics. The university has strong ties with the tech industry, providing students with ample opportunities for internships and projects.

Specializations in Computer Science

Canadian universities offer various specializations within computer science, allowing Indian students to focus on areas of interest. Some of the most popular specializations include:

Artificial Intelligence (AI): With AI transforming industries globally, Canadian universities offer specialized courses and research opportunities in AI, machine learning, and neural networks.

Cybersecurity: As cybersecurity becomes a critical concern for businesses worldwide, Canadian universities offer programs focusing on network security, cryptography, and ethical hacking.

Data Science: Data science is another rapidly growing field, and Canadian universities provide comprehensive courses on data analysis, big data, and predictive modeling.

Software Engineering: Software engineering focuses on the design, development, and maintenance of software systems, preparing students for roles in top tech companies.

Admission Requirements for Indian Students

To apply for a computer science program in Canada, Indian students typically need:

Academic Qualifications: A strong academic background in mathematics and computer science at the high school level (for undergraduate programs) or a bachelor’s degree in a related field (for postgraduate programs).

English Proficiency: Most universities require proficiency in English, demonstrated through tests like IELTS or TOEFL.

GRE/GMAT: While not always mandatory, some universities may require GRE or GMAT scores, particularly for postgraduate programs.

Work Experience: For postgraduate programs like MS or MBA in IT, relevant work experience may be beneficial.

Scholarships and Financial Aid

Many Canadian universities offer scholarships to international students, including Indian students pursuing computer science. These scholarships can be merit-based or need-based. Some popular scholarship options include:

Vanier Canada Graduate Scholarships

Ontario Graduate Scholarship

Canada-India Research Centre Scholarships

Consulting with an overseas education consultancy can help you identify suitable scholarships and guide you through the application process.

Conclusion

Canada’s computer science programs are some of the best in the world, providing Indian students with a robust education, practical experience, and strong career prospects. With a variety of specializations, world-class universities, and a booming tech industry, Canada offers endless opportunities for students looking to excel in technology. By working with an overseas education consultancy, Indian students can navigate the admission process smoothly and make the most of the opportunities available in Canada’s thriving computer science sector.

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Data science is an interdisciplinary field that combines various techniques, tools, and methodologies to extract valuable insights and knowledge from data. Datamites is an organization that offers various courses and training programs in the field of data science, artificial intelligence, and machine learning.

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Top Courses in Canada for International Students: A Comprehensive Guide

Canada is a leading destination for international students seeking high-quality education and diverse career opportunities. With its world-renowned universities, welcoming environment, and strong job market, Canada offers a variety of programs that cater to the needs of students from around the globe. In this guide, we’ll explore the top courses in Canada for international students, helping you decide which program best aligns with your academic and career goals and how overseas education consultants can save the day.

Why Canada is a top destination for international students

Before diving into the top courses in Canada, it’s important to understand why Canada is such a popular choice for international students:

World-class education: Canadian universities consistently rank among the best in the world, offering a wide range of programs known for their academic excellence.

Cultural diversity: Canada is a multicultural society that welcomes students from all backgrounds, providing a supportive environment for international learners.

Post-study work opportunities: Canada’s Post-Graduation Work Permit (PGWP) allows international students to gain valuable work experience in Canada after completing their studies.

Pathway to permanent residency: Many international students choose Canada not only for education but also for the opportunity to apply for permanent residency after graduation.

Top courses in Canada for international students

Canada offers a diverse array of programs across various fields of study. Here are some of the top courses in Canada for international students:

Engineering: Canada is known for its strong engineering programs, particularly in civil, mechanical, electrical, and computer engineering. Institutions like the University of Toronto, the University of British Columbia, and McGill University are renowned for their engineering faculties, offering cutting-edge research opportunities and industry connections.

Business and Management: Business courses in Canada, especially MBA programs, are highly sought after by international students. Schools like the Rotman School of Management, Schulich School of Business, and Sauder School of Business offer programs that are globally recognized, with specializations in finance, marketing, and entrepreneurship.

Computer Science and IT: With the growing demand for tech professionals, computer science and IT programs are among the top courses in Canada. Universities such as the University of Waterloo, the University of Toronto, and Simon Fraser University offer specialized programs in software engineering, data science, and artificial intelligence.

Health Sciences: Canada’s health sciences programs are known for their rigorous training and research opportunities. Courses in nursing, pharmacy, public health, and biomedical sciences are particularly popular, with institutions like the University of Alberta, the University of Toronto, and McMaster University leading the way.

Environmental Science: As global environmental concerns grow, Canada’s environmental science programs have gained prominence. Universities such as the University of British Columbia, Dalhousie University, and the University of Guelph offer top-tier programs that focus on sustainability, conservation, and climate change.

Hospitality and Tourism Management: Given Canada’s thriving tourism industry, hospitality and tourism management courses are also among the top choices for international students. Institutions like Ryerson University and the University of Guelph offer programs that combine academic learning with practical experience.

How to choose the right course in Canada

When selecting the best course in Canada for your needs, consider the following:

Career goals: Choose a course that aligns with your long-term career aspirations.

University reputation: Research the universities that are known for excellence in your field of interest.

Course content: Review the curriculum and ensure it covers the topics and skills you want to acquire.

Location: Consider the location of the university and whether it offers the lifestyle and opportunities you’re looking for. Consider getting in touch with overseas education consultants for better suggestions about top study destinations and programs that align with your goals.

Conclusion: Why Canada offers top courses for international students

Canada’s diverse range of top courses, combined with its welcoming environment and strong educational infrastructure, makes it an ideal destination for international students. Whether you’re interested in engineering, business, health sciences, or any other field, Canada provides a comprehensive education that can pave the way for a successful global career. By choosing one of the top courses in Canada, you’ll be investing in a bright and prosperous future.

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 Data science is a field of study that works with enormous amounts of data utilizing contemporary technologies and methodologies to uncover hidden patterns, obtain valuable information, and make business decisions. Datamites provides data science courses in the Toronto along with artificial intelligence, python, data analytics, machine learning etc.

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Top 10 Courses in Demand Globally: Universities and Career Opportunities

In today’s dynamic and evolving job market, choosing the right course of study is crucial for securing a successful and fulfilling career. Here are the top 10 courses that are in high demand globally, along with the universities offering them and the career opportunities they unlock.

Data Science and Analytics

Top Universities: Massachusetts Institute of Technology (MIT), Stanford University, University of California, Berkeley

Career Opportunities: Data Scientist, Data Analyst, Machine Learning Engineer

Computer Science and IT

Top Universities: Carnegie Mellon University, University of Cambridge, National University of Singapore

Career Opportunities: Software Developer, Cybersecurity Specialist, IT Consultant

Artificial Intelligence and Machine Learning

Top Universities: University of Oxford, California Institute of Technology (Caltech), ETH Zurich

Career Opportunities: AI Researcher, Machine Learning Engineer, Robotics Engineer

Business Administration and Management

Top Universities: Harvard Business School, INSEAD, London Business School

Career Opportunities: Business Consultant, Marketing Manager, Operations Manager

Finance and Accounting

Top Universities: University of Pennsylvania (Wharton), London School of Economics (LSE), University of Chicago (Booth)

Career Opportunities: Financial Analyst, Investment Banker, Chartered Accountant

Medicine and Healthcare

Top Universities: Johns Hopkins University, University of Toronto, University of Melbourne

Career Opportunities: Physician, Surgeon, Healthcare Administrator

Engineering (Various Disciplines)

Top Universities: Stanford University, Massachusetts Institute of Technology (MIT), University of Tokyo

Career Opportunities: Civil Engineer, Mechanical Engineer, Electrical Engineer

Law

Top Universities: Yale Law School, University of Cambridge, University of Melbourne

Career Opportunities: Lawyer, Legal Advisor, Corporate Counsel

Environmental Science and Sustainability

Top Universities: University of California, Berkeley, University of Oxford, University of British Columbia

Career Opportunities: Environmental Consultant, Sustainability Specialist, Conservation Scientist

Digital Marketing

Top Universities: University of Illinois Urbana-Champaign, University of California, Davis, IE Business School

Career Opportunities: Digital Marketing Manager, SEO Specialist, Content Strategist

These courses are designed to equip you with the skills and knowledge needed to thrive in today’s competitive job market. Top universities around the world offer specialized programs that are aligned with industry trends, ensuring that graduates are well-prepared for the future.

Ready to embark on a journey towards a rewarding career? Explore these in-demand courses with Reyna Overseas and find the right university that matches your ambitions. Your global career starts with the right education!

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Which course is best in computer coaching?

The best course in computer coaching depends on your goals, interests, and current skill level. Here are some highly recommended courses for different areas in computer science and technology:

1. Web Development

The Web Developer Bootcamp 2024 by Colt Steele (Udemy):

Covers HTML, CSS, JavaScript, Node.

Suitable for beginners to intermediate learner

Full-Stack Web Development with React Specialization (Coursera):

Offered by The Hong Kong University of Sc

Focuses on front-end and hybrid mobile development

2. Data Science and Machine Learning

Data Science Specialization (Coursera):

Offered by Johns Ho

Covers R programming, data cleaning, data analysis, and machine learning.

Machine Learning by Andrew Ng (Coursera):

Of

One of the most popular and comprehensive machine learning cour

3. Cyber security

Cybersecurity Specialization (Coursera):

Offered by the Univers

Covers the fundamentals of cybersecurity, including cryptography, hardware security, and software security.

Certified Information Systems Security Professional (CISSP) (Udemy):

Prepares you for the CISSP certification, which is highly recognized in the field of

4. Mobile App Development

iOS App Development with Swift Specialization (Coursera):

Offered by the University of Toronto.

Focuses on develop

Android App Development Specialization (Coursera):

Offered by Vanderbilt

Teaches how to develop Android applications using Java and other tools.

5. Cloud Computing

Architecting with Google Cloud Platform Specialization (Coursera):

Off

Focuses on designing, developing, and managing solutions o

AWS Certified Solutions Architect – Associate (Udemy):

Prepares you for the AWS Solutions Architect certification, covering a wide range of

6. Artificial Intelligence

Artificial Intelligence A-Z™: Learn How to Build an AI (Udemy):

Comprehensive course covering various AI concept

Deep Learning Specialization (Coursera):

Offered by DeepLearning.AI and taught by Andrew

Covers neural networks, deep learning, and related

7. *Programming Languages

Python for Everybody Specialization (Coursera):

Offered by the University of Michigan.

Excellent for beginners who want to learn Pyt

Java Programming and Software Engineering Fundamentals (Coursera):

Offe

Comprehensive course on Java programming and software engineer

8. Computer Science Fundamentals

CS50's Introduction to Computer Science (edX):

Offered by Harvard Univer

Provides a broad introduction to computer science an

Algorithms Specialization (Coursera):

Offered by Stanford University.

Covers essential algorithms and data structur

When choosing a course, consider factors such as course content, duration, instructor reputation, and student reviews. Many of these courses also offer certificates upon completion, which can be a valuable addition to your resum

TCCI Computer classes provide the best training in all computer courses online and offline through different learning methods/media located in Bopal Ahmedabad and ISCON Ambli Road in Ahmedabad.

For More Information:                   

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Visit us @ http://tccicomputercoaching.com/

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IMMIGRATION, MAMMOGRAMS, NIA

A significant amount of the courses I picked in second semester, were intentional, even if not immediately coherent, in providing me some type of exposure to the resources I know UX/UI designers and other careers use often. So in April, at the end of the semester I did a final Python based project in jupyterhub using Python to compute data, complete multiple regression analyses, make interactive maps of Toronto’s neighbourhoods with pop ups, and explore relationships between two separate statistics to see if there was a statistically significant relationship.

This research based Python project not only provided me with more confidence in coding moving forward, but also gave me a chance to see how even social sciences use coding languages in their work to help them efficiently sift for relationships that they could further investigate. Which is what I did! Combined with the results above I found papers in academic journals that also pointed to a relationship between lower sexual healthcare utilization (in this case mammograms and Pap smears) in neighbourhood improvement areas, in different age groups of women and in immigrant women to Canada. Which suggests to me that lower sexual healthcare utilization in immigrants women might be an overlooked concern that needs more support.

[itedge09]

"Certify Your Skills: Data Analyst Certification in Canada with Itedge"

Introduction

Data analysis has become an integral part of decision-making processes across industries, driving the demand for professionals with strong analytical skills. Canada, with its burgeoning tech scene and data-driven economy, offers a diverse range of courses tailored to meet the growing demand for data analysts. From foundational courses for beginners to advanced programs for experienced professionals, Canada's educational institutions provide ample opportunities for individuals looking to embark on a career in data analysis or enhance their existing skills.

Why Pursue a Data Analysis Course in Canada?

Canada has emerged as a leading destination for individuals seeking to enhance their skills in data analysis. Here are some compelling reasons why pursuing a data analysis courses in canada could be a wise decision    :

Quality Education    :    Canadian universities and colleges are renowned for their high-quality education system. Many institutions offer specialized data analysis courses that are designed to equip students with the latest tools, techniques, and methodologies used in the field.

Diverse Course Options    :    Canada provides a wide range of data analysis courses catering to various skill levels and interests. Whether you're a beginner looking for foundational knowledge or an experienced professional aiming to specialize in a particular area such as machine learning or big data analytics, there's a program suited to your needs.

Job Opportunities     :     Canada has a thriving tech sector with numerous opportunities for data analysts. Cities like Toronto, Vancouver, and Montreal are home to a burgeoning tech industry, offering a wide range of job opportunities in sectors such as finance, healthcare, e-commerce, and more.

Overview of Data Analyst Courses in Canada

Data analyst course in canada offer a comprehensive overview of the skills and knowledge necessary to excel in this rapidly growing field. These courses typically cover a wide range of topics, including statistics, data visualization, programming languages such as Python and R, database management, machine learning, and data mining techniques.

Many institutions in Canada, including universities, colleges, and online platforms, offer data analyst courses at various levels, from introductory to advanced. These courses may be part of degree programs in fields like computer science, statistics, or business, or they may be standalone certificate programs designed for professionals looking to upskill or transition into data analysis roles.

Benefits of Taking Data Analytics Courses in Ontario

Taking data analytics courses in Ontario can be highly advantageous for several reasons   :

Career Opportunities    :    With the increasing reliance on data-driven decision-making across industries, there is a growing demand for professionals skilled in data analytics. By taking data analytics courses ontario in this field, individuals can equip themselves with the necessary knowledge and skills to pursue lucrative career opportunities in various sectors such as finance, healthcare, marketing, and technology.

Skill Development    :    Data analytics courses in ontario provide hands-on training in data collection, analysis, interpretation, and visualization. These skills are not only valuable in the workplace but also in everyday life. Learning data analytics can enhance problem-solving abilities and critical thinking skills, which are essential for personal and professional growth.

Contribution to Organizational Success     :    Data analytics skills enable professionals to extract valuable insights from large datasets, helping organizations make informed decisions and optimize their operations. By taking data analytics courses, individuals can contribute to the success and growth of the organizations they work for, making them indispensable assets to their employers.

Overview of Data Analyst Courses in Canada

Different Types of Data Analysis Courses Available

In Canada, the landscape of data analysis courses in canada is diverse and evolving to meet the demands of various industries. These courses cater to a wide range of learners, from beginners seeking foundational knowledge to seasoned professionals aiming to specialize or upskill in specific areas. Here's an overview of the types of data analysis courses available across Canada   :

Foundational Data Analysis Courses   :    These courses are designed for individuals with little to no prior experience in data analysis. They typically cover fundamental concepts such as data manipulation, statistical analysis, and data visualization using popular tools like Excel, SQL, or Python.

Business Intelligence and Data Visualization    :    Courses focusing on business intelligence tools and data visualization techniques are essential for professionals looking to transform raw data into actionable insights. These courses often cover tools like Tableau, Power BI, or Google Data Studio and teach effective data storytelling techniques.

Certification Programs     :    Many institutions offer certification programs in data analysis, which provide formal recognition of proficiency in specific areas of data analysis. These certifications can enhance credibility and marketability in the job market and may focus on a particular tool, methodology, or industry.

Conclusion

The conclusion emphasizes the promising prospects that data analyst certification in canada offer. It highlights how such education serves as a gateway to a fulfilling career in a rapidly expanding industry. By underlining its relevance for both recent graduates and experienced professionals seeking to enhance their skills, it stresses the value of investing in data analysis education. Ultimately, the conclusion suggests that such investment can lead to exciting opportunities and facilitate career progression in the dynamic field of data analysis.