#Azure AI Engineer Training

[azureai102]

VisualPath in Hyderabad offers expert-led Azure AI Engineer Training to help you earn the AI-102 Certification. Our Azure AI-102 Online Course covers SQL Server, Data Science, Microsoft Azure, Generative AI, and Artificial Intelligence. With hands-on learning and real-world projects. Call +91-9989971070 to schedule your free demo session today

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Introduction to AI Platforms

AI Platforms are powerful tools that allow businesses to automate complex tasks, provide real-time insights, and improve customer experiences. With their ability to process massive amounts of data, AI platforms can help organizations make more informed decisions, enhance productivity, and reduce costs.

These platforms incorporate advanced algorithms such as machine learning, natural language processing (NLP), and computer vision to analyze data through neural networks and predictive models. They offer a broad range of capabilities such as chatbots, image recognition, sentiment analysis, and recommendation engines.

Choosing the right AI platform is imperative for businesses that wish to stay ahead of the competition. Each platform has its strengths and weaknesses which must be assessed when deciding on a vendor. Moreover, an AI platform’s ability to integrate with existing systems is critical in effectively streamlining operations.

The history of AI platforms dates back to the 1950s, with the development of early artificial intelligence research. However, over time these technologies have evolved considerably – thanks to advancements in computing power and big data analytics. While still in their infancy stages just a few years ago – today’s AI platforms have matured into complex and feature-rich solutions designed specifically for business use cases.

Ready to have your mind blown and your workload lightened? Check out the best AI platforms for businesses and say goodbye to manual tasks:

Popular Commercial AI Platforms

To explore popular the top AI platforms and make informed decisions, you need to know the benefits each platform offers. With IBM Watson, Google Cloud AI Platform, Microsoft Azure AI Platform, and Amazon SageMaker in focus, this section shows the unique advantages each platform provides for various industries and cognitive services.

IBM Watson

The Innovative AI Platform by IBM:

Transform your business with the dynamic cognitive computing technology of IBM Watson. Enhance decision-making, automate operations, and accelerate the growth of your organization with this powerful tool.

Additional unique details about the platform:

IBM Watson’s Artificial intelligence streamlines workflows and personalizes experiences while enhancing predictive capabilities. The open-source ecosystem allows developers and businesses alike to integrate their innovative applications seamlessly.

Suggested implementation strategies:

1) Leverage Watson’s data visualization tools to clearly understand complex data sets and analyze them. 2) Utilize Watson’s Natural Language processing capabilities for sentiment analysis, identifying keywords, or contextual understanding.

By incorporating IBM Watson’s versatile machine learning functions into your operations, you can gain valuable insights into customer behavior patterns, track industry trends, improve decision-making abilities, and eventually boost revenue. Google’s AI platform is so powerful, it knows what you’re searching for before you do.

Google Cloud AI Platform

The AI platform provided by Google Cloud is an exceptional tool for businesses that major in delivering machine learning services. It provides a broad array of functionalities tailored to meet the diverse demands of clients all over the world.

The following table summarizes the features and capabilities offered by the Google Cloud AI Platform:FeaturesCapabilitiesData Management & Pre-processing

– Large-scale data processing

– Data Integration and Analysis tools

– Deep Learning Frameworks

– Data versioning tools

Model Training

– Scalable training

– AutoML tools

– Advanced tuning configurations

– Distributed Training on CPU/GPU/TPU

Prediction

– High-performance responses within seconds

– Accurate predictions resulting from models trained using large-scale datasets.

Monitoring

– Real-time model supervision and adjustment

– Comprehensive monitoring, management, and optimization of models across various stages including deployment.

One unique aspect of the Google Cloud AI platform is its prominent role in enabling any developer, regardless of their prior experience with machine learning, to build sophisticated models. This ease of use accelerates experimentation and fosters innovation.

Finally, it is worth noting that according to a study conducted by International Business Machines Corporation (IBM), brands that adopted AI for customer support purposes experienced 40% cost savings while improving customer satisfaction rates by 90%.

Continue Reading

[greenoperator]

Microsoft Azure Fundamentals AI-900 (Part 1)

Microsoft Azure AI Fundamentals: Get started with artificial intelligence

Introduction to AI

Improves health care

Enables people to overcome physical disadvantages

Empowers smart infrastructure

What is AI?

foundation to AI systems

Humans teach computers and generate models

The models can make predictions and draw conclusions based on the data used to train the model

Understanding Machine Learning

Machine learning (ML) is the foundation of most AI solutions

How machine learning works

Machines learn from data!

Every day we create huge volumes of data and that data can be used to train models (text messages, emails, social media, photos, video, etc)

Data is also created by devices, sensors that are everywhere in our environment (cars, cities, factories, etc)

Data scientists use the data to train machine learning models

The models make predictions and inferences based on the relationships in the data

Machine learning in Microsoft Azure

Automated machine learning - enables non-experts to quickly create an effective machine learnings model from data

Azure machine learning designer - graphical interface enabling a no-code development environment for machine learning solution

Data and compute management - Cloud based data storage and computer resources to run data experiments at scale by professional data scientists

Pipelines - Data scientists, software engineers, and IT operations professionals can define pipelines to orchestrate model training, deployment and management tasks

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[informationcommunicationtechno]

Augmented Reality Navigation Market Share and Growth Analysis with Forecast to 2032

The Augmented Reality Navigation Market was valued at USD 1.06 billion in 2023 and is expected to reach USD 21.68 billion by 2032, growing at a CAGR of 39.97% from 2024-2032.

The Augmented Reality Navigation Market is rapidly transforming the way individuals and industries approach real-time navigation. With the integration of immersive technology and GPS-based systems, AR navigation offers interactive, intuitive, and enhanced visual guidance, making it highly effective across automotive, aviation, maritime, and pedestrian applications. As smart devices become more widespread and 5G connectivity accelerates, the demand for AR-enabled navigation tools is set to rise significantly.

Augmented Reality Navigation Market emerging space has witnessed notable growth due to advancements in mobile computing, AI, and spatial data visualization. From heads-up displays in vehicles to smart glasses for warehouse logistics, AR navigation is redefining how directions and spatial awareness are delivered. As major tech companies and startups invest heavily in this domain, the ecosystem continues to expand, paving the way for sophisticated, context-aware solutions.

Get Sample Copy of This Report: https://www.snsinsider.com/sample-request/5984 

Market Keyplayers:

Google LLC (Google Maps, ARCore)

Apple Inc. (Apple Maps, ARKit)

Microsoft (HoloLens, Azure Spatial Anchors)

WayRay AG (Navion, AR HUD)

Neusoft Corporation (Neusoft AR Navigation, Neusoft Intelligent Navigation System)

FURUNO ELECTRIC CO., LTD. (NavNet, FAR-1500 Radar System)

ARway Corp. (ARway Platform, AR Navigation Solutions)

Wiser Marine Technologies Ltd. (Wiser AR Navigation, Wiser 3D Maps)

Mapbox (Mapbox Vision, Mapbox AR)

Treedis (Treedis AR, Treedis Navigation)

ViewAR GmbH (ViewAR, ViewAR AR Navigation)

Artisense GmbH (Artisense AR, Artisense Navigation Engine)

IndoorAtlas (IndoorAtlas SDK, IndoorAtlas Positioning)

Hyper (Hyper AR, Hyper Navigation)

SITUM TECHNOLOGIES (Situm Indoor Navigation, Situm Platform)

Insider Navigation Inc (Indoor Wayfinding, Insider Navigation AR)

Wemap SAS (Wemap Indoor Navigation, Wemap AR)

Resonai Inc. (Resonai AR, Resonai Navigation Solutions)

Oriient New Media Ltd (Oriient AR, Oriient Indoor Navigation)

Navigine (Navigine AR, Navigine Indoor Navigation)

22Miles (22Miles Interactive Kiosk, 22Miles Wayfinding)

Sygic (Sygic AR Navigation, Sygic Indoor Navigation)

Veo (Veo AR, Veo Navigation)

HERE (HERE Indoor Positioning, HERE AR Navigation)

Market Analysis

The market has experienced a strong upward trajectory, supported by increasing smartphone penetration and the expansion of AR software development kits (SDKs). Automotive OEMs, logistics firms, and even tourism platforms are integrating AR to improve user experience and operational efficiency. With North America and Asia-Pacific leading in adoption, the competitive landscape is intensifying, spurring innovation and partnerships.

Scope

AR navigation finds applications in:

Automotive heads-up displays (HUDs)

Pedestrian guidance in urban areas

Indoor navigation for airports, malls, and hospitals

Military and defense training simulations

Navigation aids for the visually impaired

Trends

Integration with autonomous vehicle interfaces

Rise of AR glasses for hands-free navigation

Growing use of AI-driven route optimization

Surge in location-based advertising within AR maps

Expansion of AR applications in indoor environments

Development of multilingual AR guidance for tourism

Future Prospects

The outlook for AR navigation is bright, with continued breakthroughs in hardware, connectivity, and spatial computing. Strategic collaborations between tech giants, automakers, and app developers are expected to drive the next wave of personalized and seamless navigation experiences. As digital and physical worlds merge, AR navigation will become an everyday utility across consumer and industrial sectors.

Access Complete Report: https://www.snsinsider.com/reports/augmented-reality-navigation-market-5984 

Conclusion

With its immersive capabilities and evolving versatility, the AR Navigation Market stands at the forefront of technological evolution in spatial orientation. It promises not only to revolutionize how we navigate but also to enhance safety, efficiency, and engagement across numerous industries.

About Us:

SNS Insider is one of the leading market research and consulting agencies that dominates the market research industry globally. Our company's aim is to give clients the knowledge they require in order to function in changing circumstances. In order to give you current, accurate market data, consumer insights, and opinions so that you can make decisions with confidence, we employ a variety of techniques, including surveys, video talks, and focus groups around the world.

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Jagney Dave - Vice President of Client Engagement

Phone: +1-315 636 4242 (US) | +44- 20 3290 5010 (UK)

[health-1233]

Unlocking Innovation: The Power of Being a Microsoft Partner

In today’s rapidly evolving digital landscape, businesses across the globe are embracing technology to drive growth, enhance productivity, and stay ahead of the competition. One of the most strategic decisions a company can make to support these goals is becoming a Microsoft Partner. As a member of the Microsoft Partner Network (MPN), organizations gain access to an expansive ecosystem that empowers them to build innovative solutions, scale their services, and deliver unmatched value to their customers.

What is a Microsoft Partner?

A Microsoft Partner is a company that works with Microsoft to provide services, solutions, or support based on Microsoft technologies. These partners are part of the Microsoft Cloud Partner Program (previously known as the Microsoft Partner Network), which is designed to help businesses grow by offering resources, training, certifications, and a wide range of collaboration opportunities.

Microsoft Partners fall into various categories depending on their expertise, including:

Solutions Partners (e.g., for Infrastructure, Data & AI, Business Applications)

Independent Software Vendors (ISVs)

Managed Service Providers (MSPs)

Value-Added Resellers (VARs)

System Integrators (SIs)

Benefits of Being a Microsoft Partner

1. Access to Cutting-Edge Tools and Technologies

Microsoft Partners get early access to new software releases, development tools, and cloud services like Microsoft Azure, Microsoft 365, Dynamics 365, and more. This allows partners to stay ahead of the curve and offer up-to-date solutions.

2. Sales and Marketing Support

Partners benefit from co-selling opportunities with Microsoft, listing in the Microsoft AppSource and Azure Marketplace, and accessing marketing resources to build brand visibility and drive demand.

3. Training and Certification

Microsoft provides extensive training resources and certification programs to help partner organizations keep their teams current and competitive. Earning Microsoft credentials also enhances credibility with clients.

4. Technical Support

Being a partner includes access to dedicated support, technical advisory services, and collaboration with Microsoft engineers for troubleshooting, architecture planning, and deployment guidance.

5. Partner Designations and Specializations

Microsoft recognizes top-performing partners through designations such as Solutions Partner and Advanced Specializations. These distinctions demonstrate deep expertise in specific solution areas and enhance a partner’s reputation in the market.

Driving Digital Transformation Together

Microsoft Partners play a critical role in enabling digital transformation across industries. From helping small businesses move to the cloud to implementing enterprise-level AI-driven analytics solutions, partners are at the forefront of tech innovation.

Whether you're a consultant helping customers migrate to Azure, a developer building custom apps, or a reseller offering end-to-end managed IT services, the Microsoft Partner Program provides the tools and support needed to thrive in a competitive marketplace.

Becoming a Microsoft Partner

Joining the Microsoft Partner Program is straightforward. Interested businesses can sign up through the Microsoft Cloud Partner Program portal. Depending on your business model and focus, you can choose the right path and build your partnership level over time—from basic membership to attaining specializations and co-sell status.

[education-courses]

Data Science Meets AI: The Best Data Science Courses in India to Future-Proof Your Career 

What if you could predict the future—not just in theory, but with actual data? That’s the power of data science and AI. 

From recommending what you watch next to helping doctors detect diseases faster, data science and artificial intelligence are shaping the world around us. And as demand for skilled professionals skyrockets, the right training can open doors to some of the most in-demand and high-paying roles out there. 

In this guide, we’ll help you navigate the best data science courses in India, what to look for in a data science and AI course, and how to future-proof your career. 

Why Data Science + AI Is the Career Combo of the Decade 

In 2025, data is everywhere—and those who can make sense of it are leading the digital economy. From startups to Fortune 500 companies, organizations are relying on data scientists and AI engineers to: 

Make smarter business decisions 

Predict customer behavior 

Build intelligent systems 

Automate repetitive tasks 

Gain competitive advantages 

The result? A surge in hiring and salaries. 

According to LinkedIn, roles like “Data Scientist,” “AI Engineer,” and “Machine Learning Specialist” consistently rank among the top emerging jobs. And guess what? Many companies are hiring based on skills—not just degrees. 

What Makes a Great Data Science and AI Course? 

Whether you’re a student, a working professional, or a self-taught coder, the ideal course should tick these boxes: 

Foundational Concepts 

Understand the core pillars: statistics, Python programming, databases, and data wrangling. Without these, machine learning won’t make sense. 

Real-World Projects 

Top courses make you work on datasets from e-commerce, healthcare, finance, or social media. These help you build a job-ready portfolio. 

Machine Learning & AI Modules 

From decision trees to neural networks—your course should go beyond just the basics. Look for hands-on modules in supervised and unsupervised learning. 

Tools & Tech Exposure 

Learn to use Python, TensorFlow, NumPy, Pandas, Matplotlib, Jupyter Notebook, and cloud tools like AWS or Azure. 

Career Support 

Great courses help you not just learn, but also land. Think resume building, mock interviews, job portals, and placement support. 

Top Pick: Best Data Science Courses in India 

Looking to get started or upgrade your skills? These courses stand out: 

NIIT Digital’s Data Science and AI Program 

One of the most comprehensive and practical data science and AI courses in India. Includes: 

Core and advanced data science modules 

Live classes with industry mentors 

AI and machine learning specializations 

Capstone project 

Career support and certification 

Ideal for both beginners and professionals. 

Career Outcomes After a Data Science & AI Course 

The career paths after completing one of the best data science courses in India are as wide-ranging as they are lucrative: 

Data Analyst 

Data Scientist 

Machine Learning Engineer 

AI/ML Researcher 

Business Intelligence Developer 

AI Product Manager 

Plus, with generative AI and deep learning expanding fast, the job market is only going to grow. 

Who Should Take These Courses? 

Students & Fresh Graduates: Start strong in a future-proof field 

Career Changers: Pivot from IT, finance, or even non-tech backgrounds 

Working Professionals: Move into analytics, data roles, or AI innovation 

Developers: Level up your skills for cutting-edge tech roles 

You don’t need to be a math genius to start. Just bring curiosity and consistency. 

Learn It, Own It, Lead It 

The data revolution is happening right now—and the best part? You don’t need a PhD to be part of it. With the right data science and AI course, you can build the skills to analyze data, solve real problems, and design intelligent systems. 

Whether you’re learning to land your first role or aiming to become a data leader, NIIT Digital’s programs are built to support your goals with hands-on learning, expert guidance, and job-readiness. 

Ready to shape the future—with data at your fingertips? Explore the best data science courses in India and take your next bold career step today. 

[azureai102]

Best Azure AI Engineer Training | Azure AI-102 Online Course

Deploying & Customizing Pre-Trained Models in Azure AI Services

Introduction:

AI-102 Certification and looking to deepen your knowledge in deploying pre-trained models and customizing them through Azure AI services, you're in the right place. Azure AI Engineer Training is crucial for building and maintaining AI solutions on the Microsoft Azure platform. In this article, we will walk you through how to leverage pre-trained models, customize them, and deploy them within Azure AI services effectively. These capabilities play a vital role in creating powerful machine learning solutions, making it easier to implement AI functionality without starting from scratch.

What Are Pre-Trained Models in Azure AI?

Pre-trained models are machine learning models that have already been trained on large datasets and are optimized for specific tasks. These models are designed to handle tasks such as image recognition, natural language processing, and speech recognition. By leveraging pre-trained models, developers can save a significant amount of time, as they don't need to train models from scratch. These models come ready to use within Azure AI services like Azure Cognitive Services, which offer various APIs to integrate pre-trained capabilities into your applications.

Azure’s pre-trained models include services like:

Computer Vision: For image classification, object detection, and text extraction.

Speech: For speech recognition, speech translation, and speaker identification.

Language: For text analytics, sentiment analysis, language understanding (LUIS), and translation.

Custom Vision: A specialized service that allows users to train custom image classification models with minimal effort.

Why Use Pre-Trained Models in Azure AI?

The main advantage of using pre-trained models in Azure is their ability to expedite the AI development process. These models have already been trained on vast amounts of data, making them highly accurate and effective. They can help solve a wide range of problems across different industries, such as healthcare, finance, retail, and more. Azure AI Engineer Training equips professionals with the knowledge to effectively use these services to integrate pre-trained models into their applications.

Additionally, pre-trained models allow organizations to access state-of-the-art AI technology without the need for deep expertise in machine learning. With these models, developers can easily implement AI capabilities into their projects with just a few lines of code. As part of your AI-102 Microsoft Azure AI Training, you'll learn how to deploy and customize these models, ensuring that they meet your unique requirements.

Deploying Pre-Trained Models from Azure AI Services

When it comes to deploying pre-trained models, Azure provides several options. Azure AI Engineer Training covers these methods in detail, teaching you how to deploy models in both cloud and edge environments. Here’s how you can deploy pre-trained models in Azure:

Step 1: Choose the Right Pre-Trained Model

The first step in deploying a pre-trained model is selecting the one that fits your requirements. Azure Cognitive Services offers a variety of pre-built models tailored to specific tasks, such as vision, language, and speech. For instance, if you're building an application that needs to analyze customer feedback, the Text Analytics API might be a good fit. If your project requires image analysis, Computer Vision or Custom Vision would be ideal choices.

Step 2: Set Up Azure Resources

Once you’ve selected a model, the next step is to set up the necessary Azure resources, such as an Azure subscription, resource group, and the specific AI service. Depending on the service you’re using, you’ll need to create resources like Cognitive Services accounts, machine learning workspaces, or Azure Kubernetes Service (AKS) clusters for deploying models at scale.

Step 3: Integrate the Pre-Trained Model

With the Azure resources set up, you can now integrate the pre-trained model into your application. Azure provides SDKs for multiple programming languages, including Python, C#, and Java, to help you connect to Azure’s AI services easily. After integration, the model is ready to process input and generate predictions. For example, if you're using the Speech-to-Text API, the model can transcribe audio data into text.

Step 4: Monitor and Optimize the Deployment

Once deployed, it’s important to monitor the model’s performance in real time. Azure offers built-in monitoring tools like Azure Monitor to track key metrics such as response times, usage, and accuracy. Regular optimization ensures the model continues to deliver accurate results as your application scales.

Customizing Pre-Trained Models from Azure AI Services

While pre-trained models are powerful out of the box, there may be cases where you need to fine-tune them to better suit your specific use case. Azure AI services allow you to customize pre-trained models, making them adaptable to your needs. Customizing these models involves providing additional data to retrain them or modify their behaviour.

Customizing a Model in Azure

Collect Your Dataset: Gather a dataset that represents the unique scenarios of your application. For instance, if you're building a chatbot, you’ll need to gather examples of the phrases or questions users will ask.

Train the Model: Using Azure’s training tools, upload your data to the platform and begin training. This process involves adapting the model to learn patterns specific to your dataset.

Evaluate and Test: After training, evaluate the model to ensure its accurate and reliable. Azure provides testing tools that allow you to test your model’s predictions against known data.

Deploy the Custom Model: Once you're satisfied with the custom model’s performance, you can deploy it just like a pre-trained model.

Use Cases for Customizing Pre-Trained Models

Image Recognition: Fine-tuning pre-trained models to identify specific objects, such as brand logos or medical conditions.

Chatbots and Virtual Assistants: Customizing NLP models to better understand domain-specific jargon and user queries.

Sentiment Analysis: Adjusting language models to analyze customer feedback with a focus on industry-specific sentiments.

Conclusion

In conclusion, mastering how to deploy and customize pre-trained models is an essential skill for professionals aiming to earn the AI-102 Certification and pursue a career in Azure AI engineering. By using Azure AI Engineer Training and the tools provided by Microsoft Azure, you can effectively integrate pre-trained models into your applications, customize them for specific needs, and deploy them at scale. These skills will help you build efficient AI solutions that improve business processes, enhance user experiences, and provide valuable insights. As you progress in your AI-102 Microsoft Azure AI Training, you'll be better equipped to tackle real-world AI challenges and become an expert in Azure AI services.

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Stimulate Your Success with AI Certification Courses from Ascendient Learning

Artificial Intelligence is transforming industries worldwide. From finance and healthcare to manufacturing and marketing, AI is at the heart of innovation, streamlining operations, enhancing customer experiences, and predicting market trends with unprecedented accuracy. According to Gartner, 75% of enterprises are expected to shift from piloting AI to operationalizing it by 2024. However, a significant skills gap remains, with only 26% of businesses confident they have the AI talent required to leverage AI's full potential.

Ascendient Learning closes this skills gap by providing cutting-edge AI certification courses from leading vendors. With courses designed to align with the practical demands of the marketplace, Ascendient ensures professionals can harness the power of AI effectively.

Comprehensive AI and Machine Learning Training for All Skill Levels

Ascendient Learning’s robust portfolio of AI certification courses covers a broad spectrum of disciplines and vendor-specific solutions, making it easy for professionals at any stage of their AI journey to advance their skills. Our training categories include:

Generative AI: Gain practical skills in building intelligent, creative systems that can automate content generation, drive innovation, and unlock new opportunities. Popular courses include Generative AI Essentials on AWS and NVIDIA's Generative AI with Diffusion Models.

Cloud-Based AI Platforms: Learn to leverage powerful platforms like AWS SageMaker, Google Cloud Vertex AI, and Microsoft Azure AI for scalable machine learning operations and predictive analytics.

Data Engineering & Analytics: Master critical data preparation and management techniques for successful AI implementation. Courses such as Apache Spark Machine Learning and Databricks Scalable Machine Learning prepare professionals to handle complex data workflows.

AI Operations and DevOps: Equip your teams with continuous deployment and integration skills for machine learning models. Our courses in Machine Learning Operations (MLOps) ensure your organization stays agile, responsive, and competitive.

Practical Benefits of AI Certification for Professionals and Organizations

Certifying your workforce in AI brings measurable, real-world advantages. According to recent studies, organizations that invest in AI training have reported productivity improvements of up to 40% due to streamlined processes and automated workflows. Additionally, companies implementing AI strategies often significantly increase customer satisfaction due to enhanced insights, personalized services, and more thoughtful customer interactions.

According to the 2023 IT Skills and Salary Report, AI-certified specialists earn approximately 30% more on average than non-certified colleagues. Further, certified professionals frequently report enhanced job satisfaction, increased recognition, and faster career progression. 

Customized Learning with Flexible Delivery Options

Instructor-Led Virtual and Classroom Training: Expert-led interactive sessions allow participants to benefit from real-time guidance and collaboration.

Self-Paced Learning: Learn at your convenience with comprehensive online resources, interactive exercises, and extensive practice labs.

Customized Group Training: Tailored AI training solutions designed specifically for your organization's unique needs, delivered at your site or virtually.

Our exclusive AI Skill Factory provides a structured approach to workforce upskilling, ensuring your organization builds lasting AI capability through targeted, practical training.

Trust Ascendient Learning’s Proven Track Record

Ascendient Learning partners with the industry’s leading AI and ML vendors, including AWS, Microsoft, Google Cloud, NVIDIA, IBM, Databricks, and Oracle. As a result, all our certification courses are fully vendor-authorized, ensuring training reflects the most current methodologies, tools, and best practices.

Take Action Today with Ascendient Learning

AI adoption is accelerating rapidly, reshaping industries and redefining competitive landscapes. Acquiring recognized AI certifications is essential to remain relevant and valuable in this new era. 

Ascendient Learning provides the comprehensive, practical, and vendor-aligned training necessary to thrive in the AI-powered future. Don’t wait to upgrade your skills or empower your team.

Act today with Ascendient Learning and drive your career and your organization toward unparalleled success.

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Get Placed Faster with These Best Job Oriented Classes in Bangalore

Best Coaching Centres in Bangalore (2025),  Senfine Academy | Call  - 9845412266

Best Job-Oriented Classes in Bangalore for IT, Marketing, Finance & More

In today’s fast-paced professional landscape, upskilling is no longer a luxury—it’s a necessity. As industries evolve and new technologies emerge, job seekers and professionals alike are turning to short-term, job-oriented certification courses to stay ahead. Bangalore, known as India’s Silicon Valley, continues to be a hub for career development, offering a wide array of career-focused courses in 2025.

Whether you're a fresh graduate or a working professional looking to pivot or advance in your career, Bangalore offers diverse certification programs that cater to current market needs. Here’s a look at some of the most sought-after job-oriented courses in 2025:

1. Digital Marketing Certification

Digital marketing remains a booming sector, and with businesses expanding their online presence, demand for skilled digital marketers is at an all-time high. Courses typically cover SEO, social media marketing, Google Ads, content strategy, analytics, and email marketing. These programs are ideal for those eyeing careers in brand management, online advertising, or freelance marketing services.

2. Full Stack Development Course

Tech roles continue to dominate the job market, and full stack development is a versatile skillset highly sought after by startups and tech giants alike. Certification courses train learners in both front-end and back-end technologies, covering programming languages, database handling, and deployment. This is a great pick for anyone looking to become a software developer or tech entrepreneur.

3. Data Science and Analytics Program

Data is the new oil, and professionals who can interpret it are in demand. A certification in data science typically includes Python programming, statistics, data visualization, machine learning, and real-world project exposure. This course is ideal for individuals aiming to work as data analysts, data scientists, or AI professionals.

4. UI/UX Design Certification

As companies aim to improve user experience, UI/UX design skills are growing in demand. These courses focus on user research, wireframing, prototyping, and interaction design. Learners also gain exposure to industry-standard tools like Figma, Sketch, and Adobe XD. This creative yet strategic career path is perfect for aspiring designers and product thinkers.

5. Cybersecurity Training

With the rise of online transactions and digital businesses, cybersecurity has become critical. Certification programs in this field focus on ethical hacking, network security, malware analysis, and risk management. This course is recommended for IT professionals, network engineers, and anyone interested in protecting digital infrastructures.

6. Business Analytics Certification

Business analytics bridges the gap between IT and business strategy. These programs teach Excel modeling, SQL, business intelligence tools, and decision-making techniques. It’s a powerful course for professionals in finance, operations, or strategic planning roles.

7. Cloud Computing Certification

Cloud computing skills are essential in today’s remote-first tech world. This course teaches cloud architecture, deployment models, virtualization, and platforms like AWS, Microsoft Azure, and Google Cloud. Ideal for IT professionals looking to boost their infrastructure or DevOps credentials.

Final Thoughts

The job market in 2025 is evolving rapidly, and Bangalore continues to lead as a center for professional advancement. Choosing a certification course that aligns with your interests and career goals can give you the competitive edge needed to succeed.

These job-oriented courses not only enhance your technical and soft skills but also boost your employability in top industries such as IT, marketing, finance, and design. Whether you're looking to transition careers or climb the ladder in your current role, now is the perfect time to invest in yourself.

[sid099]

Why You Should Hire MLOps Developers for Scalable AI Solution

New version: MLOps (Machine Learning Operations) developers are needed to take lab-based machine learning models and apply them to real-world production settings. They integrate the expertise of data scientists, software engineers, and DevOps specialists to guarantee that ML models are scalable and reliable and continuously improving.

These developers automate every step of the machine learning lifecycle, from data preparation and model training to deployment, monitoring, and version control. Through the use of tools like Kubernetes, Docker, MLflow, and various cloud platforms (such as AWS, Azure, and GCP), MLOps developers assist companies in accelerating model deployment and reducing time to market. MLOps Developers: Filling the Void Between Operations and Machine Learning MLOps (machine learning operations) developers are essential for transferring lab-based machine learning models into actual production settings. They integrate the expertise of data scientists, software engineers, and DevOps specialists to guarantee that ML models are scalable, dependable, and always evolving. The ML lifecycle, which consists of data preparation, model training, deployment, monitoring, and version control, must be automated by these developers. Through the use of cloud platforms (AWS, Azure, GCP) and tools like Kubernetes, Docker, and MLflow, MLOps developers assist businesses in expediting model deployment and cutting down on time to market.

[dypiucollege]

MCA Specialisations: Which One is Right for You?

MCA is considered one of the most preferred postgraduate courses by aspirants who intend to work in the rapid growth of computers and technology. As industries continue to digitise quickly, there is a growing demand for MCA graduates, particularly in IT, banking, healthcare and e-commerce. 

However, selecting the right MCA specialisation is essential for your career choice. Whether you want to be a software developer, data scientist, cybersecurity expert, or IT consultant, choosing the best specialisation can give you an edge. 

In this blog post, we will discuss the most popular MCA courses, career opportunities, and how to choose the best option for you.

1. MCA in Software Development

Software Development is the perfect choice if you love coding and want to develop innovative software solutions. This major develops the skills to build websites and applications, database design and management, programming languages, software engineering, etc.

Key Subjects:

Object-Oriented Programming (OOP)

Web and Mobile App Development

Database Management Systems (DBMS)

Cloud Computing

Software Testing and Quality Assurance

Career Opportunities:

Software Developer

Full-Stack Developer

Application Engineer

Web Developer

Cloud Software Engineer

This specialisation is perfect for those who enjoy problem-solving and have a knack for writing efficient code.

2. MCA in Data Science & Big Data Analytics

As data-driven decision-making revolutionises the modern business era, data science and prominent data analytics professionals are in great demand. This MCA specialisation trains students in machines, statistical modelling, data analysis, and artificial intelligence.

Key Subjects:

Data Mining and Warehousing

Machine Learning and AI

Predictive Analytics

Deep Learning

Big Data Technologies (Hadoop, Spark)

Career Opportunities:

Data Scientist

Machine Learning Engineer

Business Intelligence Analyst

Data Engineer

If you love working with numbers and extracting insights from large datasets, this specialisation is an excellent choice.

3. MCA in Cyber Security & Ethical Hacking

Cyber threats are growing, and cybersecurity is one of the most pivotal areas in IT. This specialisation trains students to secure digital assets, discover vulnerabilities and defend networks from attackers.

Key Subjects:

Network Security

Ethical Hacking

Cryptography

Information Security Management

Digital Forensics

Career Opportunities:

Cyber Security Analyst

Ethical Hacker

Information Security Consultant

Security Architect

It is the best field for cybersecurity lovers and ethical hackers to protect the digital world.

4. MCA in Cloud Computing

Cloud computing is changing the IT landscape, making it a high-grossing career choice. This specialisation trains students to design, implement and manage applications and services that are built on cloud-based systems.

Key Subjects:

Cloud Architecture

Virtualisation Technologies

AWS, Google Cloud, Microsoft Azure

DevOps Practices

Cloud Security

Career Opportunities:

Cloud Solutions Architect

Cloud Security Analyst

DevOps Engineer

Cloud Engineer

This specialisation is for you if you want to manage and optimise cloud platforms.

5. MCA in Artificial Intelligence & Machine Learning

This specialisation is part of a series on the innovations made possible by the AI/ML revolution, which makes industries in health, finance and beyond work differently when they are on. This specialisation encompasses designing intelligent systems that can learn and adapt.

Key Subjects:

Neural Networks

Deep Learning

Natural Language Processing (NLP)

Robotics & Automation

AI-driven Business Solutions

Career Opportunities:

AI Engineer

Machine Learning Scientist

NLP Engineer

Robotics Engineer

This specialisation provides endless opportunities for those fascinated by automation and intelligent computing.

6. MCA in Blockchain Technology

How blockchain is changing the way we look at things in business. The MCA specialisation trains students to develop secure and decentralised applications.

Key Subjects:

Blockchain Fundamentals

Smart Contracts Development

Cryptography and Distributed Ledger Technology

Decentralised Applications (DApps)

Career Opportunities:

Blockchain Developer

Cryptocurrency Analyst

Smart Contract Developer

Blockchain Consultant

Blockchain is a path to embrace if you are an enabler of disruptive technology and decentralisation.

7. MCA in Internet of Things (IoT)

IoT, or the Internet of Things, encapsulates connecting natural physical elements with the web, helping create competent answers for homes, medical help, and industrial automation. This specialisation includes networking, data analytics, and embedded systems.

Key Subjects:

IoT Architecture and Protocols

Embedded Systems

Wireless Sensor Networks

IoT Security

Career Opportunities:

IoT Developer

Embedded Systems Engineer

Smart Home Automation Specialist

IoT Security Analyst

This specialisation is excellent if you love innovation and working with smart devices.

8. MCA in IT Management

IT Management is for those who wish to get the best of both worlds of technology and business. It focuses on IT project management, enterprise / solution and business intelligence.

Key Subjects:

IT Strategy and Governance

Enterprise Resource Planning (ERP)

Business Analytics

IT Risk Management

Career Opportunities:

IT Manager

Business Analyst

Technology Consultant

IT Project Manager

This specialisation is ideal for those looking to take on leadership roles in the IT sector.

9. MCA in Game Development

The Game Development industry is on the rise, and there is an immensely high demand for professionals in this domain. These specialisations include game design, graphics programming, and immersive technology.

Key Subjects:

Game Engine Programming (Unity, Unreal)

AR/VR Development

Computer Graphics

Game Testing and Debugging

Career Opportunities:

Game Developer

AR/VR Developer

Game Designer

Simulation Engineer

This specialisation can be a dream career path for those passionate about gaming and creativity.

How to Choose the Right MCA Specialisation?

Choosing the right MCA specialisation depends on several factors, including:

Your Interests: What excites you the most? Coding, security, AI, or management?

Career Goals: Do you want to be a developer, data scientist, or IT manager?

Industry Demand: Research job market trends to identify high-demand fields.

Skillset: Align your technical strengths with the specialisation that suits you.

Final Thoughts

There are various specialisations in an MCA, all leading to different careers. The right specialisation for you would be the one that helps you realise your career goals, be it software development, cybersecurity, AI engineering, etc. Research the top MCA colleges and career prospects before deciding, but most importantly, go for the field you are interested in. If you choose the right MCA specialisation, you can build a successful and rewarding career in the tech industry. Whether you're aiming to get into the best MCA colleges or already exploring top MCA colleges, making an informed choice can set the stage for a bright future.

[informationcommunicationtechno]

Data Collection and Labeling Market Growth Forecast and Industry Share Report 2032

The Data Collection And Labeling Market was valued at USD 3.0 Billion in 2023 and is expected to reach USD 29.2 Billion by 2032, growing at a CAGR of 28.54% from 2024-2032.

The Data Collection and Labeling Market plays a foundational role in enabling the development of machine learning (ML) and artificial intelligence (AI) technologies. As businesses increasingly rely on AI-driven systems for automation, prediction, and decision-making, the demand for accurately labeled datasets has surged. This process, which involves gathering raw data and annotating it to make it usable for training models, is crucial across a wide spectrum of industries including automotive, healthcare, retail, finance, and robotics.

The Data Collection and Labeling Market continues to evolve with the growing complexity of AI models and the need for high-quality, domain-specific data. Organizations are seeking scalable and efficient solutions to collect, structure, and enrich massive datasets for applications ranging from computer vision and speech recognition to sentiment analysis and fraud detection. The market encompasses a variety of services including image and video annotation, text and audio transcription, as well as data classification and segmentation.

Get Sample Copy of This Report: https://www.snsinsider.com/sample-request/5925 

Market Keyplayers:

Scale AI – Scale Data Engine

Appen – Appen Data Annotation Platform

Labelbox – Labelbox AI Annotation Platform

Amazon Web Services (AWS) – Amazon SageMaker Ground Truth

Google – Google Cloud AutoML Data Labeling Service

IBM – IBM Watson Data Annotation

Microsoft – Azure Machine Learning Data Labeling

Playment (by TELUS International AI) – Playment Annotation Platform

Hive AI – Hive Data Labeling Platform

Samasource – Sama AI Data Annotation

CloudFactory – CloudFactory Data Labeling Services

SuperAnnotate – SuperAnnotate AI Annotation Tool

iMerit – iMerit Data Enrichment Services

Figure Eight (by Appen) – Figure Eight Data Labeling

Cogito Tech – Cogito Data Annotation Services

Market Analysis

Driven by advancements in AI and the proliferation of smart devices, the market is undergoing significant transformation. Enterprises and tech startups alike are investing heavily in curated datasets that feed algorithms with meaningful insights. The increasing adoption of supervised learning techniques has intensified the demand for accurately labeled data, particularly in sectors such as autonomous driving, diagnostic imaging, and natural language processing.

Crowdsourcing platforms, in-house labeling teams, and third-party vendors are all integral to the ecosystem. The market is also seeing a shift toward semi-automated and AI-assisted labeling tools to address scalability and reduce human error. While data privacy and quality assurance remain challenges, innovative solutions are continuously emerging to enhance security and compliance.

Scope

The scope of the market spans multiple data types and industry applications. Key services include:

Image/Video Labeling – Used in facial recognition, surveillance, AR/VR, and driver assistance systems

Text Annotation – For chatbot training, document classification, and contextual analysis

Audio Transcription – Applied in voice assistants, speech analytics, and call center optimization

Sensor Data Annotation – Crucial in robotics, industrial automation, and IoT applications

Verticals utilizing data labeling solutions include healthcare, automotive, fintech, e-commerce, education, and entertainment. The shift toward edge AI, real-time analytics, and multilingual AI solutions is further broadening the market's relevance.

Market Forecast

The demand for data annotation is expected to escalate in alignment with the exponential growth of AI-powered systems. With the evolution of generative AI, conversational agents, and autonomous technologies, the need for diverse, high-quality training data is becoming more strategic than ever. The integration of synthetic data generation and automated labeling tools is expected to complement traditional methods, creating a hybrid ecosystem.

Markets in Asia-Pacific, particularly India and China, are emerging as global hubs for data labeling services due to their tech talent pool and cost-efficiency. Meanwhile, North America and Europe are focusing on innovation and regulatory compliance, fueling demand for secure, high-fidelity data labeling frameworks.

Future Prospects

Looking ahead, the market will witness a fusion of human intelligence and machine precision. Ethical AI, explainability, and bias mitigation are likely to become standard components of data labeling protocols. Additionally, the emergence of data-centric AI, where model performance is improved through better data rather than algorithm tweaks, will prioritize labeling accuracy and relevance.

Startups and enterprises alike will benefit from plug-and-play labeling solutions integrated with cloud-based ML platforms. Government initiatives to support AI research and data governance will further influence market dynamics and service standards.

Key Trends

AI-Assisted Labeling Tools – Enhancing speed and reducing human workload

Synthetic Data Generation – Creating labeled data for edge cases and rare scenarios

Vertical-Specific Labeling Services – Tailored solutions for industries like healthcare and automotive

Data-Centric AI Approaches – Focus on improving model performance through better data quality

Privacy-Preserving Labeling – Incorporation of federated learning and differential privacy

Scalable Workforce Platforms – Hybrid human-machine systems for large-scale projects

Access Complete Report: https://www.snsinsider.com/reports/data-collection-and-labeling-market-5925 

Conclusion

In essence, the Data Collection and Labeling Market forms the bedrock of AI innovation, bridging raw data with actionable intelligence. As enterprises pursue deeper AI integration, demand for precise, scalable, and ethically sourced labeled data will accelerate, solidifying the market’s role in the digital transformation era.

About Us:

SNS Insider is one of the leading market research and consulting agencies that dominates the market research industry globally. Our company's aim is to give clients the knowledge they require in order to function in changing circumstances. In order to give you current, accurate market data, consumer insights, and opinions so that you can make decisions with confidence, we employ a variety of techniques, including surveys, video talks, and focus groups around the world.

Contact Us:

Jagney Dave - Vice President of Client Engagement

Phone: +1-315 636 4242 (US) | +44- 20 3290 5010 (UK)

[futurensetechnologies]

Big Data Technologies You’ll Master in IIT Jodhpur’s PG Diploma

In today’s digital-first economy, data is more than just information—it's power. Successful businesses are set apart by their ability to collect, process, and interpret massive datasets. For professionals aspiring to enter this transformative domain, the IIT Jodhpur PG Diploma offers a rigorous, hands-on learning experience focused on mastering cutting-edge big data technologies.

Whether you're already in the tech field or looking to transition, this program equips you with the tools and skills needed to thrive in data-centric roles.

Understanding the Scope of Big Data

Big data is defined not just by volume but also by velocity, variety, and veracity. With businesses generating terabytes of data every day, there's a pressing need for experts who can handle real-time data streams, unstructured information, and massive storage demands. IIT Jodhpur's diploma program dives deep into these complexities, offering a structured pathway to becoming a future-ready data professional.

Also, read this blog: AI Data Analyst: Job Role and Scope

Core Big Data Technologies Covered in the Program

Here’s an overview of the major tools and technologies you’ll gain hands-on experience with during the program:

1. Hadoop Ecosystem

The foundation of big data processing, Hadoop offers distributed storage and computing capabilities. You'll explore tools such as:

HDFS (Hadoop Distributed File System) for scalable storage

MapReduce for parallel data processing

YARN for resource management

2. Apache Spark

Spark is a game-changer in big data analytics, known for its speed and versatility. The course will teach you how to:

Run large-scale data processing jobs

Perform in-memory computation

Use Spark Streaming for real-time analytics

3. NoSQL Databases

Traditional databases fall short when handling unstructured or semi-structured data. You’ll gain hands-on knowledge of:

MongoDB and Cassandra for scalable document and column-based storage

Schema design, querying, and performance optimization

4. Data Warehousing and ETL Tools

Managing the flow of data is crucial. Learn how to:

Use tools like Apache NiFi, Airflow, and Talend

Design effective ETL pipelines

Manage metadata and data lineage

5. Cloud-Based Data Solutions

Big data increasingly lives on the cloud. The program explores:

Cloud platforms like AWS, Azure, and Google Cloud

Services such as Amazon EMR, BigQuery, and Azure Synapse

6. Data Visualization and Reporting

Raw data must be translated into insights. You'll work with:

Tableau, Power BI, and Apache Superset

Custom dashboards for interactive analytics

Real-World Applications and Projects

Learning isn't just about tools—it's about how you apply them. The curriculum emphasizes:

Capstone Projects simulating real-world business challenges

Case Studies from domains like finance, healthcare, and e-commerce

Collaborative work to mirror real tech teams

Industry-Driven Curriculum and Mentorship

The diploma is curated in collaboration with industry experts to ensure relevance and applicability. Students get the opportunity to:

Attend expert-led sessions and webinars

Receive guidance from mentors working in top-tier data roles

Gain exposure to the expectations and workflows of data-driven organizations

Career Pathways After the Program

Graduates from this program can explore roles such as:

Data Engineer

Big Data Analyst

Cloud Data Engineer

ETL Developer

Analytics Consultant

With its robust training and project-based approach, the program serves as a launchpad for aspiring professionals.

Why Choose This Program for Data Engineering?

The Data Engineering course at IIT Jodhpur is tailored to meet the growing demand for skilled professionals in the big data industry. With a perfect blend of theory and practical exposure, students are equipped to take on complex data challenges from day one.

Moreover, this is more than just academic training. It is IIT Jodhpur BS./BSc. in Applied AI and Data Science, designed with a focus on the practical, day-to-day responsibilities you'll encounter in real job roles. You won’t just understand how technologies work—you’ll know how to implement and optimize them in dynamic environments.

Conclusion

In a data-driven world, staying ahead means being fluent in the tools that power tomorrow’s innovation. The IIT Jodhpur Data Engineering program offers the in-depth, real-world training you need to stand out in this competitive field. Whether you're upskilling or starting fresh, this diploma lays the groundwork for a thriving career in data engineering.

Take the next step toward your future with “Futurense”, your trusted partner in building a career shaped by innovation, expertise, and industry readiness.

Source URL: www.lasttrumpnews.com/big-data-technologies-iit-jodhpur-pg-diploma

[anandtechverceseo]

Why Chennai Is a Thriving Tech Hub

Chennai has rapidly emerged as one of India’s foremost technology hubs, offering a dynamic ecosystem for businesses to thrive. From startups to multinational corporations, organizations seeking scalable and cost‑effective solutions turn to the best software development company in Chennai. With a robust talent pool, advanced infrastructure, and a supportive business environment, Chennai consistently delivers top‑tier software services that cater to global standards.

Understanding a Software Development Company in Chennai

A Software Development Company in Chennai brings together expertise in multiple domains—custom application development, enterprise software, mobile apps, and emerging technologies like AI, IoT, and blockchain. These firms typically follow agile methodologies, ensuring timely delivery and iterative improvements. Here’s what you can expect from a leading Chennai‑based software partner:

Full‑Stack Development: End‑to‑end solutions covering front‑end frameworks (React, Angular, Vue) and back‑end technologies (Node.js, .NET, Java, Python).

Mobile App Engineering: Native (Swift, Kotlin) and cross‑platform (Flutter, React Native) mobile development for iOS and Android.

Cloud & DevOps: AWS, Azure, and Google Cloud deployments, automated CI/CD pipelines, containerization with Docker and Kubernetes.

Quality Assurance & Testing: Manual and automated testing services to ensure reliability, performance, and security.

UI/UX Design: User‑centric interfaces that prioritize accessibility, responsiveness, and engagement.

What Sets the Best Software Development Company in Chennai Apart

Talent and Expertise Chennai’s educational institutions and coding bootcamps produce a steady stream of skilled engineers. The best software development companies in Chennai invest heavily in continuous training—ensuring teams stay up‑to‑date with the latest frameworks, security protocols, and best practices.

Cost‑Effectiveness Without Compromise By leveraging competitive operational costs and local talent, Chennai firms offer attractive pricing models—fixed‑bid, time‑and‑materials, or dedicated teams—without sacrificing quality. Many global clients report savings of 30–40% compared to Western markets, while still benefiting from seasoned professionals.

Strong Communication and Transparency English proficiency is high among Chennai’s tech workforce, facilitating clear requirements gathering and regular progress updates. Top companies implement robust project‑management tools (Jira, Trello, Asana) and schedule daily stand‑ups, sprint reviews, and monthly road‑map sessions to keep you in the loop.

Cutting‑Edge Infrastructure Chennai’s IT parks and technology corridors, such as TIDEL Park and OMR’s “IT Corridor,” are equipped with world‑class facilities—high‑speed internet, reliable power backup, and on‑site data centers. This infrastructure underpins uninterrupted development and deep collaboration between distributed teams.

Commitment to Security and Compliance Whether handling GDPR‑sensitive data, implementing PCI‑DSS standards for e‑commerce, or conducting regular penetration testing, the best software development companies in Chennai prioritize security. ISO‑certified processes and ISMS frameworks ensure your project adheres to global compliance requirements.

How to Choose the Right Partner

Portfolio and Case Studies Review a prospective partner’s past work—industry verticals, technology stacks, scalability achievements, and client testimonials. Look for success stories in your domain to validate domain‑specific expertise.

Engagement Model Decide whether you need a project‑based model, a dedicated offshore team, or staff augmentation. The best software development company in Chennai will offer flexible engagement options aligned with your budget and timelines.

Technical Interviews and Audits Conduct technical screenings or request code audits to assess coding standards, architecture decisions, and test coverage. An open��book approach to code review often signals confidence in quality.

Cultural Fit and Long‑Term Vision Beyond technical prowess, ensure cultural alignment—communication styles, work ethics, and shared goals. A partner who understands your long‑term roadmap becomes a strategic extension of your in‑house team.

Conclusion

Choosing the best software development company in Chennai means tapping into a vibrant tech ecosystem fueled by innovation, cost‑efficiency, and a commitment to excellence. Whether you’re launching a new digital product or modernizing legacy systems, a Software Development Company in Chennai can deliver tailor‑made solutions that drive growth and empower your business for the digital age. Reach out today to explore how Chennai’s top tech talent can transform your vision into reality.