Hari Thapliyaal

Dr. Hari Thapliyal is a seasoned professional and prolific blogger with a multifaceted background that spans the realms of Data Science, Project Management, and Advait-Vedanta Philosophy. Holding a Doctorate in AI/NLP from SSBM (Geneva, Switzerland), Hari has earned Master’s degrees in Computers, Business Management, Data Science, and Economics, reflecting his dedication to continuous learning and a diverse skill set.

With over three decades of experience in management and leadership, Hari has proven expertise in training, consulting, and coaching within the technology sector. His extensive 16+ years in all phases of software product development are complemented by a decade-long focus on course design, training, coaching, and consulting in Project Management.

In the dynamic field of Data Science, Hari stands out with more than three years of hands-on experience in software development, training course development, training, and mentoring professionals. His areas of specialization include Data Science, AI, Computer Vision, NLP, complex machine learning algorithms, statistical modeling, pattern identification, and extraction of valuable insights.

Hari’s professional journey showcases his diverse experience in planning and executing multiple types of projects. He excels in driving stakeholders to identify and resolve business problems, consistently delivering excellent results. Beyond the professional sphere, Hari finds solace in long meditation, often seeking secluded places or immersing himself in the embrace of nature.

3 minute read

GenAI for AI-Assisted Programming

Program Outline: AI Assisted Programming

Duration:

4 Days

Course Audience:

Technical Leads, Technical Architects, Service Delivery Managers

Target Unit:

Delivery CoE, Product, Internal Applications

Course Outline

Day 1: Foundations of AI-Assisted Programming

Morning Sessions 9:00 AM to 1:00 PM

1. Session 1 - Introduction to AI-Assisted Programming (9:00 AM - 10:30 AM)

  • Overview of AI in Software Development
  • Key Benefits of AI-Assisted Tools for Developers

2. Session 2 - Understanding Code Generators (10:45 AM - 1:00 PM)

  • Introduction to Tools like GitHub Copilot and ChatGPT
  • Exploring Use Cases: Boilerplate Code, Debugging, and Optimization

Lunch 1:00 PM to 2:00 PM

Afternoon Sessions 2:00 PM to 5:00 PM

3. Session 3 - Hands-on with GitHub Copilot (2:00 PM - 3:30 PM)

  • Setting Up and Configuring GitHub Copilot
  • Writing and Refining Code with AI Assistance

4. Session 4 - Collaborative Programming with AI (3:45 PM - 5:00 PM)

  • Pair Programming: AI as a Virtual Coding Partner
  • Best Practices for Effective Human-AI Collaboration

Day 2: Advanced AI-Assisted Programming

Morning Sessions 9:00 AM to 1:00 PM

5. Session 5 - Natural Language Processing (NLP) for Programming (9:00 AM - 10:30 AM)

  • How NLP Powers AI-Assisted Tools
  • Enhancing Code Search and Documentation

6. Session 6 - AI for Code Review and Testing (10:45 AM - 1:00 PM)

  • Using AI to Automate Code Reviews
  • Tools for Generating and Running Test Cases

Lunch 1:00 PM to 2:00 PM

Afternoon Sessions 2:00 PM to 5:00 PM

7. Session 7 - Debugging with AI Assistance (2:00 PM - 3:30 PM)

  • Identifying Bugs and Suggesting Fixes with AI
  • Debugging Examples and Use Cases

8. Session 8 - Exploring Code Refactoring with AI (3:45 PM - 5:00 PM)

  • Simplifying Complex Code Structures
  • Improving Code Readability and Maintainability

Day 3: AI in Real-World Development Scenarios

Morning Sessions 9:00 AM to 1:00 PM

9. Session 9 - AI-Assisted API Development (9:00 AM - 10:30 AM)

  • Generating APIs and Integrating with Existing Systems
  • Hands-on Activity: Building APIs with AI

10. Session 10 - AI in Cloud and DevOps (10:45 AM - 1:00 PM)

  • Automating CI/CD Pipelines with AI
  • AI for Cloud Resource Management

Lunch 1:00 PM to 2:00 PM

Afternoon Sessions 2:00 PM to 5:00 PM

11. Session 11 - AI for Frontend and UX Development (2:00 PM - 3:30 PM)

  • Using AI to Generate Responsive Designs
  • Improving User Interfaces with AI Feedback

12. Session 12 - Building AI-Powered Applications (3:45 PM - 5:00 PM)

  • Incorporating AI Features in Applications
  • Examples and Case Studies

Day 4: Integrating and Mastering AI-Assisted Tools

Morning Sessions 9:00 AM to 1:00 PM

13. Session 13 - Customizing AI Tools for Your Team (9:00 AM - 10:30 AM)

  • Configuring Tools to Fit Development Needs
  • Adapting AI for Organization-Specific Use Cases

14. Session 14 - Ethical AI and Developer Responsibility (10:45 AM - 1:00 PM)

  • Addressing Bias and Data Privacy Concerns
  • Understanding the Limits of AI in Development

Lunch 1:00 PM to 2:00 PM

Afternoon Sessions 2:00 PM to 5:00 PM

15. Session 15 - Capstone Project: AI-Assisted Development (2:00 PM - 4:00 PM)

  • Team Activity: Solve a Real-World Development Challenge Using AI Tools

16. Session 16 - Feedback and Future Trends (4:00 PM - 5:00 PM)

  • Discussion: Evolving AI Technologies for Programming
  • Participant Presentations and Closing Remarks

Key Outcomes:

  • Understand the fundamentals and capabilities of AI-assisted programming tools.
  • Enhance coding efficiency, accuracy, and collaboration through AI tools.
  • Learn practical techniques for debugging, testing, and API development with AI.
  • Develop a project leveraging AI-assisted tools tailored to real-world scenarios.
  • Basic familiarity with programming languages (e.g., Python, JavaScript).
  • Explore GitHub Copilot or ChatGPT for developers (optional).
  • Review examples of AI-generated code and test cases.

Materials Provided:

  • Comprehensive course slides and handouts.
  • Access to AI tools and trial subscriptions.
  • Links to further learning resources.
  • Certificate of Completion.

Updated:

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