Course Description

Learn the coding fundamentals needed to build and deploy AI Agents. This hands-on course covers codes and  APIs, perfect for beginners and professionals entering the world of AI and AI Agents.

Course curriculum

  • 1
    Introduction to Python
    • Introduction to the Course
    • Overview of Python
    • Quiz
    • Variables and Data Types + Codes
    • Quiz
    • Understanding Conditional Statements + Codes
    • Quiz
    • Implementing Conditional Statements
    • Functions in Python - Part 2
    • Quiz
    • Recommended Reading Materials
  • 2
    Loops and Functions in Python
    • Understanding Looping Constructs
    • Looping Constructs
    • Functions in Python
    • Modules and Packages in Python
    • Quiz
    • Hands on: Python Best Practices
  • 3
    Exploring Python Libraries
    • The Basics of NumPy
    • Hands-on: The Basics of NumPy
    • Arithmetic Universal Functions in NumPy
  • 4
    Data Visualization with Matplotlib and Pandas
    • The Basics of Matplotlib: Types of Plots
    • The Basics of Matplotlib: Customizing Plots
    • The Basics of Pandas: Understanding the Dataset
    • Handling Missing Values and Modifying the Dataset
    • Quiz
  • 5
    Working with APIs
    • Working with APIs
    • Quiz
    • Accessing APIs using Python
    • Quiz
    • API Best Practices

Who Should Enroll?

  • Aspiring AI Developers – Gain essential coding skills to create and deploy AI models and applications.

  • Tech Enthusiasts & Beginners – Learn coding for AI from scratch and unlock the potential of Generative AI technologies.

  • Professionals Upskilling in AI – Boost your career with AI programming expertise and improve your ability to work with AI tools and machine learning models.

Key Takeaways

  • Understand core programming concepts relevant to python, including variables, functions, data types, etc.

  • Build and integrate AI solutions using APIs.

About the Instructor

Prashant Sahu - Data Science Manager || Certified Generative AI Specialist || Experienced AI Leader & Coach for ML, DL, and NLP || PhD @ IIT-Bombay

Prashant Sahu is the Data Science Manager at Analytics Vidhya, with extensive expertise in AI, ML, and advanced analytics. He has led high-impact B2B pre-sales initiatives and developed comprehensive training programs for top clients, including HSBC, JP Morgan Chase, and Reliance Industries. Prashant’s technical expertise spans the Python ecosystem, deep learning, Generative AI, NLP, and model deployment. He has also created innovative solutions like the "Mentorship Web App" and the "Article Recommendation System." In his current role, he manages data science projects, evaluates training programs, and oversees content quality for flagship programs like BlackBelt and Pinnacle GenAI.
About the Instructor

FAQs

  • Q. Who is this course for?

    A. This course is designed for beginners who want to build a solid foundation in AI programming, as well as professionals looking to expand their knowledge of AI technologies and coding essentials.

  • Q. What programming languages will be covered in this course?

    A. The course focuses on core programming concepts that are essential for working with AI, primarily using Python, which is widely used in AI and machine learning applications.

  • Q. Do I need any prior experience with coding or AI?

    A. No prior experience is required. This course starts with the basics, making it suitable for those new to coding as well as those with some experience looking to learn about AI programming.

  • Q. Will I learn how to build AI models in this course?

    A. While this course provides a strong coding foundation for working with AI, it focuses more on understanding AI concepts like prompt engineering, APIs, and frameworks, rather than building complex AI models from scratch.

  • Q. How will this course help me in my career?

    A. By mastering essential coding skills for AI, you'll gain the ability to work with AI tools and frameworks, which are in high demand across industries. This course will help you build the skills needed to start developing and integrating AI solutions into real-world projects.