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Humanity will have to re-invent itself

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Guided meditation with a talk about finding INNER PEACE - TRUE LOVE - FR...

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Complete Data Wrangling & Data Visualisation In R

THIS IS YOUR ROADMAP TO LEARNING & BECOMING HIGHLY PROFICIENT IN DATA PREPROCESSING, DATA WRANGLING, & DATA VISUALIZATION IN R!

Hello, My name is Minerva Singh. I am an Oxford University MPhil graduate in Geography & Environment & I  finished a PhD at Cambridge University in Tropical Ecology & Conservation.

I have +5 of experience in analyzing real-life data from different sources using statistical modelling and producing publications for international peer-reviewed journals. If you find statistics books & manuals too vague, expensive & not practical, then you’re going to love this course!

I created this course to take you by hand and teach you all the concepts, and tackle the most fundamental building block on practical data science - data wrangling and visualisation.

THIS COURSE WILL TEACH YOU ALL YOU NEED AND PUT YOUR KNOWLEDGE TO PRACTICE NOW!

This course is your sure-fire way of acquiring the knowledge and statistical data analysis wrangling and visualisation skills that I acquired from the rigorous training I received at 2 of the best universities in the world, the perusal of numerous books and publishing statistically rich papers in the renowned international journal like PLOS One.

HERE IS WHAT THIS COURSE WILL DO FOR YOU:

It will take you (even if you have no prior statistical modelling/analysis background) from a basic level of performing some of the most common data wrangling tasks in R.

It will equip you to use some of the most important R data wrangling and visualisation packages such as dplyr and ggplot2.

It will Introduce some of the most important data visualisation concepts to you in a practical manner such that you can apply these concepts for practical data analysis and interpretation.

You will also be able to decide which wrangling and visualisation techniques are best suited to answer your research questions and applicable to your data and interpret the results..

The course will mostly focus on helping you implement different techniques on real-life data such as Olympic and Nobel Prize winners

After each video, you will learn a new concept or technique which you may apply to your own projects immediately! Reinforce your knowledge through practical quizzes and assignments.

ON TOP OF THE COURSE, I’M ALSO OFFERING YOU:

Practice Activities To Reinforce Your Learning

My Continuous Support To Make Sure You Gain Complete Understanding & Proficiency

Access To Future Course Updates Free Of Charge

I’ll Even Go The Extra Mile & Cover Any Topics That Are Related To The Subject That You Need Help With (This is something you can’t get anywhere else).

& Access To A Community Of 25,000 Data Scientists (& growing) All Learning Together & Helping Each Other!

Now, go ahead & enrol in the course. I’m certain you’ll love it, but in case you don’t, you can always request a refund within 30 days. No hard feelings whatsoever. I look forward to seeing you inside!

Who this course is for:

Students Interested In Getting Started With Data Science Applications In The R & R Studio Environment

Students Interested in Learning About the Common Pre-processing Data Tasks: Including Cleaning and Munging

Students Interested in Gaining Exposure to Common R Packages Such As ggplot2

Those Interested in Learning About Different Kinds of Data Visualisations

Those Interested in Learning to Create Publication Quality Visualisations.

92% discount #coupon #udemy #course for Complete Data #Wrangling & #Data #Visualisation In R #couponcode https://www.udemy.com/complete-data-wrangling-data-visualization-with-r/

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Tensorflow and Keras For Neural Networks and Deep Learning

THIS IS A COMPLETE NEURAL NETWORKS & DEEP LEARNING TRAINING WITH TENSORFLOW & KERAS IN PYTHON!

It is a full 7-Hour Python Tensorflow & Keras Neural Network & Deep Learning Boot Camp that will help you learn basic machine learning, neural networks and deep learning  using two of the most important Deep Learning frameworks- Tensorflow and Keras.                        

HERE IS WHY YOU SHOULD ENROLL IN THIS COURSE:

This course is your complete guide to practical machine & deep learning using the Tensorflow & Keras framework in Python..

This means, this course covers the important aspects of Keras and Tensorflow (Google's powerful Deep Learning framework) and if you take this course, you can do away with taking other courses or buying books on Python Tensorflow and Keras based data science.  

In this age of big data, companies across the globe use Python to sift through the avalanche of information at their disposal and advent of Tensorflow and Keras is revolutionizing Deep Learning...

By gaining proficiency in Keras and and Tensorflow, you can give your company a competitive edge and boost your career to the next level.

THIS IS MY PROMISE TO YOU: COMPLETE THIS ONE COURSE & BECOME A PRO IN PRACTICAL KERAS & TENSORFLOW BASED DATA SCIENCE!

But first things first. My name is Minerva Singh and I am an Oxford University MPhil (Geography and Environment) graduate. I recently finished a PhD at Cambridge University (Tropical Ecology and Conservation).

I have several years of experience in analyzing real life data from different sources  using data science related techniques and producing publications for international peer reviewed journals.

Over the course of my research I realized almost all the Python data science courses and books out there do not account for the multidimensional nature of the topic and use data science interchangeably with machine learning..

This gives students an incomplete knowledge of the subject. My course, on the other hand, will give you a robust grounding in all aspects of data science within the Tensorflow framework.

Unlike other Python courses, we dig deep into the statistical modeling features of Tensorflow & Keras and give you a one-of-a-kind grounding in these frameworks!

DISCOVER 8 COMPLETE SECTIONS ADDRESSING EVERY ASPECT OF PYTHON BASED TENSORFLOW DATA SCIENCE:

• A full introduction to Python Data Science and powerful Python driven framework for data science, Anaconda • Getting started with Jupyter notebooks for implementing data science techniques in Python • A comprehensive presentation about Tensorflow & Keras installation and a brief introduction to the other Python data science packages • Brief introduction to the working of Pandas and Numpy • The basics of the Tensorflow syntax and graphing environment • The basics of the Keras syntax • Machine Learning, Supervised Learning, Unsupervised Learning in the Tensorflow & Keras frameworks • You’ll even discover how to create artificial neural networks and deep learning structures with Tensorflow & Keras

BUT,  WAIT! THIS ISN'T JUST ANY OTHER DATA SCIENCE COURSE:

You’ll start by absorbing the most valuable Python Tensorflow and Keras basics and techniques.

I use easy-to-understand, hands-on methods to simplify and address even the most difficult concepts.

My course will help you implement the methods using real data obtained from different sources. Many courses use made-up data that does not empower students to implement Python based data science in real -life.

After taking this course, you’ll easily use packages like Numpy, Pandas, and Matplotlib to work with real data in Python along with gaining fluency in Tensorflow and Keras. I will even introduce you to deep learning models such as Convolution Neural network (CNN) !!

The underlying motivation for the course is to ensure you can apply Python based data science on real data into practice today, start analyzing  data for your own projects whatever your skill level, and impress your potential employers with actual examples of your data science abilities.

This course will take students without a prior Python and/or statistics background background from a basic level to performing some of the most common advanced data science techniques using the powerful Python based Jupyter notebooks

It is a practical, hands-on course, i.e. we will spend some time dealing with some of the theoretical concepts related to data science. However, majority of the course will focus on implementing different  techniques on real data and interpret the results..

After each video you will learn a new concept or technique which you may apply to your own projects!

JOIN THE COURSE NOW!

Who this course is for:

People Interested In Learning Python Based Tensorflow and Keras For Data Science Applications

People With Prior Exposure To Python Programming &/Or Data Science Concepts

People Interested In Implementing Neural Networks & Deep Learning Models With Tensorflow

People Interested In Implementing Neural Networks & Deep Learning Models With Keras.

92% discount #coupon #udemy #course for #Tensorflow and Keras For Neural Networks and #Deep #Learning #couponcode https://www.udemy.com/tensorflow-and-keras-for-neural-networks-and-deep-learning/

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Clustering & Classification With Machine Learning In R

HERE IS WHY YOU SHOULD TAKE THIS COURSE:

This course your complete guide to both supervised & unsupervised learning using R...

That means, this course covers all the main aspects of practical data science and if you take this course, you can do away with taking other courses or buying books on R based data science.

In this age of big data, companies across the globe use R to sift through the avalanche of information at their disposal. By becoming proficient in unsupervised & supervised learning in R, you can give your company a competitive edge and boost your career to the next level.

LEARN FROM AN EXPERT DATA SCIENTIST WITH +5 YEARS OF EXPERIENCE:

My name is Minerva Singh and I am an Oxford University MPhil (Geography and Environment) graduate. I recently finished a PhD at Cambridge University.

I have +5 years of experience in analyzing real life data from different sources using data science related techniques and producing publications for international peer reviewed journals.

Over the course of my research I realized almost all the R data science courses and books out there do not account for the multidimensional nature of the topic...

This course will give you a robust grounding in the main aspects of machine learning- clustering & classification.

Unlike other R instructors, I dig deep into the machine learning features of R and gives you a one-of-a-kind grounding in  Data Science!

You will go all the way from carrying out data reading & cleaning  to machine learning to finally implementing powerful machine learning algorithms and evaluating their performance using R.

THIS COURSE HAS 8 SECTIONS COVERING EVERY ASPECT OF R MACHINE LEARNING:

• A full introduction to the R Framework for data science

• Data Structures and Reading in R, including CSV, Excel and HTML data

• How to Pre-Process and “Clean” data by removing NAs/No data,visualization

• Machine Learning, Supervised Learning, Unsupervised Learning in R

• Model building and selection...& MUCH MORE!

By the end of the course, you’ll have the keys to the entire R Machine Learning Kingdom!

NO PRIOR R OR STATISTICS/MACHINE LEARNING KNOWLEDGE REQUIRED:

You’ll start by absorbing the most valuable R Data Science basics and techniques. I use easy-to-understand, hands-on methods to simplify and address even the most difficult concepts in R.

My course will help you implement the methods using real data obtained from different sources. Many courses use made-up data that does not empower students to implement R based data science in real life.

After taking this course, you’ll easily use data science packages like caret to work with real data in R...

You’ll even understand concepts like unsupervised learning, dimension reduction and supervised learning. Again, we'll work with real data and you will have access to all the code and data used in the course.

JOIN MY COURSE NOW!

Who this course is for:

Students Interested In Getting Started With Data Science Applications In The R & R Studio Environment

Students Wishing To Learn The Implementation Of Unsupervised Learning On Real Data

Students Wishing To Learn The Implementation Of Supervised Learning (Classification) On Real Data Using R.

92% discount #coupon #udemy #course for #Clustering & #Classification With #Machine #Learning In R #couponcode https://www.udemy.com/clustering-classification-with-machine-learning-in-r/

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ArcGIS Desktop For Spatial Analysis: Go From Basic To Pro

I WANNA LEARN SPATIAL DATA ANALYSIS, BUT…

I found most spatial data books & manuals vague

There are no courses that actually teach me how it’s actually done

Available resources are expensive & I can’t afford them

I want to get a job in the field of GIS and geospatial analysis

I work in the field of ecology or quantitative social sciences or hydrology or civil engineering or geography

If you found yourself in one of these situations, then..

I’VE GOT GREAT NEWS FOR YOU!

Over the past few months, I have published multiple courses on Udemy around this topic which will be tremendously helpful to you & most important of all AFFORDABLE!

Today, I’ve created yet another powerful resource for you!

In this course, over 50+ hands-on and practical lecture, I will help you master the most common and important geo-processing tasks that can be performed with ArcGIS Desktop, one of THE MOST important GIS software tools available.

I will also show you the kind of questions answered through Spatial Analysis & data used.

THE STEPS I’LL WALK YOU THROUGH:

First of all, we’ll start some basic GIS tasks like “Zooming”.

Then, we’ll move into more complex processing tasks like “Geo-Statistics”.

We’ll also deal with some theoretical concepts related to Spatial Data Analysis, and then we’ll focus on implementing some of the most common GIS techniques (all the way showing you how to execute these tasks in ArcGIS Desktop).

The stuff you’ll learn from this course will be extremely useful in terms of you being able to implement it on future Spatial Data projects you’ll be working on (in a variety of disciplines from ecology to engineering).

LEARN FROM AN ACTUAL EXPERT IN THIS AREA:

My name is MINERVA SINGH.

I am an Oxford University MPhil (Geography and Environment) graduate.

I recently finished my PhD at Cambridge University (Tropical Ecology and Conservation).

I have SEVERAL YEARS OF EXPERIENCE in analyzing REAL LIFE DATA from different sources in ArcGIS Desktop.

I’ve also published my work in many international peer reviewed journals.

HERE IS HOW MY COURSE IS UNIQUE..

My course is a HANDS ON TRAINING with REAL data.

It’s a step by step course covering both the THEORY & APPLICATION of Spatial Data Analysis.

I teach Practical Stuff that you can learn quickly and start implementing NOW.

This is one of the most comprehensive courses on this topic.

I advise you to take advantage of it & enroll in the course TODAY!

TAKE ACTION TODAY! I will personally support you and ensure your experience with this course is a success. I answer all questions put to me and guide my students when they get stuck.

Please make sure you have access to ArcGIS before enrolling

Who this course is for:

Academics and Researchers

Conservation managers, field ecologists and social scientists

People looking to get started in the field of GIS Analysis

Students of Geography, Environmental Sciences, Geology, Hydrology, Engineering, Earth Sciences and Ecology

People looking to use ArcGIS Desktop in academic or professional settings.

#ArcGIS Desktop For Spatial Analysis: Go From Basic To Pro #udemy #course 95% off !!! #couponcode https://www.udemy.com/arcgis-desktop-for-spatial-analysis-go-from-basic-to-pro/?couponCode=ARCGIS10A

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Project Based Python Programming For Kids & Beginners

Beginners and Kids Can Now Learn Python the Fun and Easy Way

Teach yourself (and your kids) to code fun games, graphics and GUI in Python, the powerful programming language used at tech companies and in academia.

Unlike the other courses and books out there, this course provides a rare opportunity to learn the graphics and UX (User Experience) sides of Python – even as a beginner! Unlike the many other Python courses on Udemy, this course introduces you to this computer language by drawing shapes, coding a simple game, and designing GUIs (Graphic User Interfaces), including a functional GUI for a temperature converter app.

Gain a Firm Foundation in Python GUI Programming

Learn the basics of Python game programming

Craft elegant and useful Python GUIs

Create simple and practical applications in Python

Explore the world of Python graphic design

If you want to learn to code, Python GUIs are the best way to start!

I designed this programming course to be easily understood by absolute beginners and young people. We start with basic Python programming concepts. Reinforce the same by developing games, graphics and GUIs. And finally we will develop a practical temperature converter app using Python.

Why Python?

The Python coding language integrates well with other platforms – and runs on virtually all modern devices. If you’re new to coding, you can easily learn the basics in this fast and powerful coding environment. If you have experience with other computer languages, you’ll find Python simple and straightforward. This OSI-approved open-source language allows free use and distribution – even commercial distribution.

Can You Build a Career with Python?

Absolutely! On average, U.S. Python developers earn $109,000 per year. This powerful and widely-used language could be your or your child's ticket to a better life. With the rigorous grounding you get from this course, you’ll have the knowledge and confidence to step into higher-level Python courses.

How Can You Use Python?

Once you gain a basic knowledge of Python through this course, you can explore a diverse range of programming specialties:

Build Desktop/Laptop GUIs

Design Exciting and Immersive Games

Develop Websites and Apps

Analyze Scientific and Statistical Data

Create Educational Software

Access and Organize Databases

Manage Networks

Who Uses Python?

This course gives you a solid set of skills in one of today’s top programming languages. Today’s biggest companies (and smartest startups) use Python, including Google, Facebook, Instagram, Amazon, IBM, and NASA. Python is increasingly being used for scientific computations and data analysis.

You Can Start Right Away, Without Prior Programming Experience

Detailed instructions have been provided with regards to Python installation and getting started with Microsoft Visual Code, a powerful programming IDLE that will be a valuable tool for your programming journey. Hands-on coding instructions have been provided in the lecture videos to enable you to follow along. Additionally, working code examples have been provided for you to try and modify. Each video will teach you a new practical programming concept that you can apply in real time and quizzes will reinforce your learning.

The instructor is an Oxbridge trained researcher and always available to troubleshoot. You'll also receive an industry recognized Certificate of Completion upon finishing the course.

No Risk: Preview videos from the different sections for FREE, and enjoy a 30-day money-back guarantee when you enroll - zero risk, unlimited payoff!

Sign up for this course today and learn the skills you need to rub shoulders with today’s tech industry giants. Have fun, create and control intriguing and interactive Python GUIs, and enjoy a bright future!

Who this course is for:

Anyone who wants to learn to code

People wanting to program in Python

People interested in gaining hands-on Python skills and actually wanting to work through real life programming projects

People interested in building games and GUIs

Anyone looking to start with Python GUI development

Programming beginners and children who want to create practical applications.

Project Based #Python #Programming For #Kids & #Beginners  90% OFF ! #coupon for UDEMY COURSE https://www.udemy.com/project-based-python-programming-for-kids-beginners/?couponCode=PYTHONLEARN10A

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Beginners python data analytics : Data science introduction : Learn data science : Python data analysis methods tutorial

Beginners python data analytics : Data science introduction : Learn data science : Python data analysis methods tutorial

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Data Science:Data Mining & Natural Language Processing in R

MASTER DATA SCIENCE, TEXT MINING AND NATURAL LANGUAGE PROCESSING IN R:

Learn to carry out pre-processing, visualization and machine learning tasks such as: clustering, classification and regression in R. You will be able to mine insights from text data and Twitter to give yourself & your company a competitive edge.    

                              LEARN FROM AN EXPERT DATA SCIENTIST  WITH +5 YEARS OF EXPERIENCE:

My name is Minerva Singh and I am an Oxford University MPhil (Geography and Environment) graduate. I recently finished a PhD at Cambridge University (Tropical Ecology and Conservation). I have several years of experience in analyzing real life data from different sources using data science related techniques and producing publications for international peer reviewed journals. Over the course of my research I realized almost all the R data science courses and books out there do not account for the multidimensional nature of the topic and use data science interchangeably with machine learning. This gives students an incomplete knowledge of the subject. Unlike other courses out there, we are not going to stop at machine learning. We will also cover data mining, web-scraping, text mining and natural language processing along with mining social media sites like Twitter and Facebook for text data.

                                 NO PRIOR R OR STATISTICS/MACHINE LEARNING KNOWLEDGE IS REQUIRED:

You’ll start by absorbing the most valuable R Data Science basics and techniques. I use easy-to-understand, hands-on methods to simplify and address even the most difficult concepts in R. My course will help you implement the methods using real data obtained from different sources. Many courses use made-up data that does not empower students to implement R based data science in real life. After taking this course, you’ll easily use packages like caret, dplyr to work with real data in R. You will also learn to use the common NLP packages to extract insights from text data.   I will even introduce you to some very important practical case studies - such as detecting loan repayment and tumor detection using machine learning. You will also extract tweets pertaining to trending topics and analyze their underlying sentiments and identify topics with Latent Dirichlet allocation. With this Powerful All-In-One R Data Science course, you’ll know it all: visualization, stats, machine learning, data mining, and neural networks!  

The underlying motivation for the course is to ensure you can apply R based data science on real data into practice today. Start analyzing data for your own projects, whatever your skill level and Impress your potential employers with actual examples of your data science projects.

HERE IS WHAT YOU WILL GET:

(a) This course will take you from a basic level to performing some of the most common advanced data science techniques using the powerful R based tools.  

(b) Equip you to use R to perform the different exploratory and visualization tasks for data modelling.  

(c) Introduce you to some of the most important machine learning concepts in a practical manner such that you can apply these concepts for practical data analysis and interpretation.   (d) You will get a strong understanding of some of the most important data mining, text mining and natural language processing techniques.  

(e) & You will be able to decide which data science techniques are best suited to answer your research questions and applicable to your data and interpret the results.

More Specifically, here's what's covered in the course:

Getting started with R, R Studio and Rattle for implementing different data science techniques

Data Structures and Reading in Pandas, including CSV, Excel, JSON, HTML data.

How to Pre-Process and “Wrangle” your R data by removing NAs/No data, handling conditional data, grouping by attributes..etc

Creating data visualizations like histograms, boxplots, scatterplots, barplots, pie/line charts, and MORE

Statistical analysis, statistical inference, and the relationships between variables.

Machine Learning, Supervised Learning, & Unsupervised Learning in R

Neural Networks for Classification and Regression

Web-Scraping using R

Extracting text data from Twitter and Facebook using APIs

Text mining

Common Natural Language Processing techniques such as sentiment analysis and topic modelling

We will spend some time dealing with some of the theoretical concepts related to data science. However, majority of the course will focus on implementing different techniques on real data and interpret the results.

After each video you will learn a new concept or technique which you may apply to your own projects.

All the data and code used in the course has been made available free of charge and you can use it as you like. You will also have access to additional lectures that are added in the future for FREE.

JOIN THE COURSE NOW!

Who this course is for:

Students wishing to learn practical data science and machine learning in R

Students wishing to learn the underlying theory and application of data mining in R

Students interested in obtaining/mining data from sources such as Twiter

Students interested in pre-processing and visualizing real life data

Students wishing to analyze and derive insights from text data

Students interested in learning basic text mining and Natural Language Processing (NLP) in R.

94% off !!! #udemy #course for #Data #Science :Data Mining & Natural Language Processing in R Harness the Power of Machine Learning in R for Data/Text Mining, & Natural Language Processing with Practical Examples #coupon #deal https://www.udemy.com/data-science-datamining-natural-language-processing-in-r/?couponCode=DATAMINE1

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Applied Statistical Modeling for Data Analysis in R

APPLIED STATISTICAL MODELING FOR DATA ANALYSIS IN R

COMPLETE GUIDE TO STATISTICAL DATA ANALYSIS & VISUALIZATION FOR PRACTICAL APPLICATIONS IN R

            Confounded by Confidence Intervals? Pondering Over p-values? Hankering Over Hypothesis Testing?

Hello, My name is Minerva Singh and I am an Oxford University MPhil (Geography and Environment) graduate. I recently finished a PhD at Cambridge University (Tropical Ecology and Conservation).

I have several years of experience in analyzing real life data from different sources using statistical modeling and producing publications for international peer reviewed journals. If you find statistics books & manuals too vague, expensive & not practical, then you’re going to love this course!

I created this course to take you by hand and teach you all the concepts, and take your statistical modeling from basic to an advanced level for practical data analysis.

With this course, I want to help you save time and learn what the arcane statistical concepts have to do with the actual analysis of data and the interpretation of the bespoke results. Frankly, this is the only one course you need to complete  in order to get a head start in practical statistical modeling for data analysis using R.

My course has 9.5 hours of lectures and provides a robust foundation to carry out PRACTICAL, real-life statistical data analysis tasks in R, one of the most popular and FREE data analysis frameworks.

GET ACCESS TO A COURSE THAT IS JAM PACKED WITH TONS OF APPLICABLE INFORMATION! AND GET A FREE VIDEO COURSE IN MACHINE LEARNING AS WELL!

This course is your sure-fire way of acquiring the knowledge and statistical data analysis skills that I acquired from the rigorous training I received at 2 of the best universities in the world, perusal of numerous books and publishing statistically rich papers in renowned international journal like PLOS One.

To be more specific, here’s what the course will do for you:

 (a) It will take you (even if you have no prior statistical modelling/analysis background) from a basic level to performing some of the most common advanced statistical data analysis tasks in R.

 (b) It will equip you to use R for performing the different statistical data analysis and visualization tasks for data modelling.

 (c) It will Introduce some of the most important statistical concepts to you in a practical manner such that you can apply these concepts for practical data analysis and interpretation.

 (d) You will learn some of the most important statistical modelling concepts from probability distributions to hypothesis testing to regression modelling and multivariate analysis.

 (e) You will also be able to decide which statistical modelling techniques are best suited to answer your research questions and applicable to your data and interpret the results.

The course will mostly focus on helping you implement different statistical analysis techniques on your data and interpret the results.

After each video you will learn a new concept or technique which you may apply to your own projects immediately!

TAKE ACTION NOW :) You’ll also have my continuous support when you take this course just to make sure you’re successful with it.  If my GUARANTEE is not enough for you, you can ask for a refund within 30 days of your purchase in case you’re not completely satisfied with the course.

TAKE ACTION TODAY! I will personally support you and ensure your experience with this course is a success.

Who this course is for:

People working in any numerate field which requires data analysis

Students of Environmental Science, Ecology, Biology,Conservation and Other Natural Sciences

People with some prior knowledge of the R interface- (a) installing packages (b) reading in csv files

People carrying out observational or experimental studies.

95% off !! Applied Statistical Modeling for Data Analysis in R #udemy course online #couponcode https://www.udemy.com/applied-statistical-modeling-for-data-analysis-in-r/?couponCode=AUGDISC10