With IR 4.0 technology being rapidly adopted across all industries and trades, the job roles are also transitioning from the traditional ones. To quickly adapt to this transition in the job market and be ready to take up the available jobs, getting the right set of skills needed for these jobs is of utmost importance. The most ubiquitous new job roles are related to the technologies of Artificial Intelligence, Cloud Computing, and Web Design, hence the modules being delivered in this program are also related to these skills. 

In a Total of  24 weeks, 100 hours of instructor led core technical training content, 20 hours of self-paced employability skills, and 40 hours of individualized review content is delivered as part of the program.

The core technical content breakdown has been delineated below.

Vertical 1: Artificial Intelligence

  • Introduction to AI and understanding different AI terminologies  
  • Understanding the evolution of AI and the AI winter cycle 
  • The AI applications transforming various industries 
  • Current AI market trends and opportunities 
  • Chatbot fundamentals  
  • Building and hosting a chatbot 
  • Introduction to Linux Kernel and vital role of Linux in application development  
  • Working with Linux shell commands and different Linux text editors for Shell scripting 
  • Managing Linux files, users and permissions 
  • Data Science vs Data Analysis vs Data Analytics 
  • Working with Python for Data Science  
  • Python packages for Data Analytics applications  
  • NumPy  
  • Matplotlib  
  • Pandas 
  • Data Analysis use cases 
  • Introduction to Artificial Neural Networks (ANN), Deep Neural Networks (DNN) and Deep Learning (DL) 
  • Understanding how DL helps solve classical Machine Learning limitations 
  • Implementation of deep learning networks like CNN with TensorFlow  
  • Deep learning use cases 
  • Perceptron model and Learning rule  
  • Deep neural networks and its components  
  • Understanding how DL helps solve classical Machine Learning limitations 
  • Implementation of deep learning networks like CNN with TensorFlow  
  • Deep learning use cases 
  1. Computer vision applications with OpenCV and OpenVINO toolkit  
  • Introduction to computer vision and its applications  
  • Developing computer vision applications with OpenCV  
  • Computer vision use cases  
  • Deep learning model optimization and deployment for inference at the edge with OpenVINO toolkit  

    2. Natural Language processing with Python
  • Introduction to NLP  
  • NLP applications, market trends and opportunities 
  • Classification of NLP 
  • Working with python packages to develop NLP applications  
  • NLP use cases  

    3. Text based Chatbot development
  • Introduction to chatbots  
  • Chatbot applications, market trends and opportunities 
  • Understanding chatbot architecture  
  • Development and deployment of text based chatbots 

Vertical 2: Cloud Computing

    • Cloud computing evolution, challenges and opportunities  
    • Cloud computing fundaments and classifications   
    • Characteristics of Cloud Computing  
    • Cloud Deployment Model  
    • Cloud Service Delivery Model 
    • Cloud Global Infrastructures  
  • Azure Core Services and its classifications  
  • Microsoft Azure Cognitive Services  
  • Building applications with azure cognitive services 
    • Customer Managed IaaS  
    • Fully Managed PaaS  
    • Serverless Applications (Code-Only)  
    • Introduction to Containers  
    • Container vs VM  
    • Docker Containers  
    • Container Images and Repositories  
    • Container Orchestration using Kubernetes  
  • Challenges related to AI implementations  
  • Solutions from Microsoft Azure for AI implementation  
  • Computation Made Easy  
  • Analytics is more fun  
  • Data Management is a game  
  • Automation at its best  

Vertical 3: Web Design and Digital Marketing

  • Web application components and classification of web applications
  • HTML for web Layout
  • CSS for Page Design
  • JS for Client-side scripting 
    • Understanding Server-Side Scripting 
    • Web application dev with PHP, Syntax, semantics, data types, variables, flow control and loop control 
    • Handling Client-side data using PHP 
    • Managing Sessions at Server and Cookies at Client 
    • Creating sessions, session data, reading and writing cookies at client side 
      • Introduction to relational databases- MySQL 
      • Introducing relational databases, need for database, persistent storage benefits, MySQL basics, commands 
      • Handling databases 
      • CRUD operations using SQL, DDL and DML 
      • Managing data in databases using PHP 
      • Connecting to MySQL DB using PHP, performing CRUD operations using PHP, persistent storage of front-end data to MySQL DB 
  • ReactJS framework, develop using React components and single page applications 
  • JQuery for web application development, using component properties and dynamic handling of pages 
  • Quick dive into digital marketing fundamentals  
  • Digital marketing trends, challenges and opportunities, web elements involved, scope in web development 
  • Applying the DM concepts in web 
  • Search Engine Optimization (SEO) for websites/ webapps, connecting through social media, routing and landing to marketing strategic locations on web 

Industry Certifications

Industry certification courses offered by openSAP and MS   This part of the program gives students an opportunity to optionally earn industry certifications for various courses offered by SAP  through their  openSAP  platform that offers innovative learning for everyone free of cost.  Microsoft has also launched global skills initiative to bring more digital skills worldwide. Students will be encouraged to audit relevant courses from these two platforms free of charge. List of the recommended course will be shared with the students.   These two platforms can be accessed using the links given below:  
  1. OpenSAP:  Free SAP Training | openSAP 
  2. MS Global Skill Initiative: AI Engineers on Microsoft Learn | Microsoft Docs