ATC-AIF - Gen AI Fundamentals


Duration: 1.0 day

Artificial Intelligence (AI) and Machine Learning (ML) today are the most sought-after skills in the digital economy.

We find use of AI in multiple categories which include self-driving cars, web searching and speech recognition programs.

We use AI numerous times every day and the results which we will observe with the automated approaches available for human betterment and decision making.

This course includes theory, hands-on projects.

You also get practical know-how to apply the AI and ML tools and techniques and provide essential AI and ML knowledge and skills to several AI concepts and workflows.


  • To learn about AI and its applications
  • Learn about the impact and current usability of AI
  • AI Industry adoption today in multiple domains and Industry.
  • Understand how ML, Deep Learning and Neural Networks works with practical examples.
  • Steps to build career in AI
  • Learn workflows and how to implement and its methods


Module 1: Introduction to AI

1.1 What is Artificial Intelligence?

1.2 Brief History and Evolution of AI

1.3 Type of AI

1.4 AI Applications and Impact on Various Industries (Healthcare , BFSI, Law ,Retail ,Advertising & Media, Automotive & Transportation, Regional Insights, Market scope Insights)

1.5 Ethical and Social Implications of AI

1.6 AI Tools

Module 2: AI In Cloud

1.7 What is cloud computing?

1.8 Deployment model Vs Service model

1.9 Introduction to Azure , AWS and GCP

1.10 AI Tools in Cloud

Activity – Familiarization of cloud AI tools

Module 3: Machine Learning Fundamentals

3.1 Introduction to Machine Learning

3.2 Framing an ML problem.

3.3 Data Preprocessing and Feature Engineering

3.4 Model Selection, Training, and Evaluation

3.5 Types of Machine Learning: Supervised, Unsupervised, Reinforcement

3.3.1 Regression

3.3.2 Classification

3.3.3 Clustering

3.6 Overfitting, Underfitting, and Regularization

3.7 Evaluation Metrics in Machine Learning

Activity - Create a Regression Model

Activity - Create a Classification Model

Activity - Create a Clustering Model

Module 4: Neural Networks and Deep Learning

4.1 Basics of Neural Networks

4.2 Activation Functions and Network Architectures

4.3 Training Deep Neural Networks

4.4 Convolutional Neural Networks (CNNs)

4.5 Recurrent Neural Networks (RNNs)

Activity -Image recognition

Module 5: Natural Language Processing (NLP)

5.1 Introduction to NLP

5.2 Text Preprocessing and Tokenization

5.3 Sentiment Analysis and Text Classification

5.4 Machine Translation

5.5 NLP Applications

Activity – Create chatbot using no-code or low code solution

Module 6: Computer Vision

6.1 What is Computer Vision?

6.2 How does Computer Vision Work?

6.3 The evolution of computer vision

6.4 Applications of computer vision

6.5 Challenges of computer vision

Activity – Create Computer vision application using no-code or low code solution

Module 7: Future of AI and Emerging Trends

7.1 Current State of AI Research and Development

7.2 Open Challenges and Opportunities in AI

7.3 Generative AI Vs Open AI


Anyone who is a beginner at AI or wants to learn about AI, Students, Scientist, Engineers. This program is beneficial to professionals from a variety of industries and backgrounds. Those who are looking for a career into the field of AI and ML, who have knowledge or prior experience in programming and mathematics, and an analytical frame of mind will be added advantage.


There are no prerequisites to learning this Artificial Intelligence course. This course has been designed to cater to the understanding level of beginners. This course does not require any programming or computer science expertise and is designed to introduce the basics of AI to anyone whether you have a technical background or not.



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