Generative AI Syllabus: What to Study?

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Generative AI Syllabus

A comprehensive generative AI syllabus acts like a roadmap. It tells you what essential topics you should study, what skills you should develop, and what you should expect from the subject. This way, you can plan your studies and make sure you don’t miss anything important.

In this blog post, I will break down the generative AI syllabus of Ivy Professional School’s IIT-certified GenAI course. You will understand what topics you should learn and in what order to easily master this AI technology.

 

The Latest Generative AI Syllabus: 9 Essential Modules

If you want to become a generative AI expert, you can join Ivy Pro’s GenAI Certification course, which is made in partnership with E&ICT Academy, IIT Guwahati. 

The course follows the following detailed syllabus designed by industry experts. It focuses not only on in-demand skills but also on interesting industry projects. This way, you gain solid practical experience and the confidence to face real-world problems. 

1. Programming Fundamentals

This module covers the basics of Python programming, which is important for building generative AI apps. It starts with setting up Python, including installation and IDE configuration. 

Then, you learn about Python data types such as strings, integers, lists, and dictionaries, followed by control flow, loops, and functions. You also learn libraries like Pandas and Numpy for data manipulation. 

The module covers hands-on projects like creating functions for a recommendation system and preparing data for AI model training using Pandas.

 

2. Introduction to Generative AI

In this module, you are introduced to the core concepts of AI and generative AI. Here, you understand what makes generative models unique. 

The module covers various types of generative models and provides an overview of OpenAI APIs, particularly focusing on their application in text generation. 

Then, you work on a project where you use Python to interact with OpenAI APIs to generate text. 

Related: 7 Must-Read Generative AI Books 

 

3. Machine Learning Fundamentals

This module introduces the basics of machine learning. You learn linear models, decision trees, and k-nearest neighbors (k-NN) to build both classification and regression models.

The hands-on projects help you create and evaluate models using multiple algorithms to ensure robustness and accuracy. 

Next, you start with deep learning. You learn what it is, the important concepts in it, and activation functions and optimizers. 

The syllabus takes you through different deep learning architectures, such as Multi-Layer Perceptrons (MLPs), Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Long Short-Term Memory (LSTM) networks. 

The hands-on project helps you build models for tasks like object detection and image classification using CNNs. 

 

4. Building a Chatbot 

You know AI chatbots? They are AI-powered software programs that can understand natural language and speak just like humans. In this module of the generative AI syllabus, you build an AI chatbot. Interesting, right?

It starts with the basics of chatbots- what they are and how they work. You learn to design chatbot workflows using flowcharts and user interactions. You also learn how Large Language Models (LLMs) and Generative AI can be combined for chatbot development. 

Then, you set up a Python environment, install the necessary libraries, and initialize a chatbot project. You also practice generating and refining conversational prompts, responses, and logic. 

You fine-tune the chatbot using real-world data, optimizing its performance and evaluating its effectiveness.

The module concludes with a capstone project where you deploy your chatbot on a web platform, integrating it with OpenAI’s API for real-time interaction.

5. Building a Social Media Automation Tool

In this module, you create an AI tool for social media automation. It begins with an introduction to automating social media tasks and understanding how to generate text and images for these platforms.

Then, you learn to implement LangChain components within this tool to streamline content generation and management. Then, you construct a search index and entity store to enhance content retrieval. 

You also develop scripts to generate and schedule social media posts using OpenAI APIs. Then, you deploy the generative AI tool on a cloud platform, ensuring it operates smoothly.

Additionally, this fifth module of the generative AI syllabus covers the basics of resume creation using AI.

You learn how to generate personalized resume content using OpenAI APIs and style it using Python libraries like ReportLab or PDFKit. Finally, you develop and deploy this AI tool.

 

6. Image Generation

In this module, you build an AI tool that can generate product images for e-commerce.

It starts with an overview of the image requirements in e-commerce, such as product photos, catalogs, and customization options. 

Then, you generate product images, variations, and customizations using the DALL-E API, which you learn to integrate and configure for seamless use.

The module also covers automating image uploads using Python scripts for batch processing, image transformation, and optimization. 

You also learn to implement serverless computing with cloud functions for scalable and efficient image management.

The module concludes with a capstone project where you implement DALL-E for dynamic image generation tailored specifically for e-commerce platforms.

 

7. Building a Voice Assistant

In this module of the generative AI syllabus, you build a voice assistant that can recognize and generate voice like humans.

First, you learn about the components of voice recognition systems, including audio processing, feature extraction, and pattern recognition. Then, you implement basic voice recognition algorithms. 

Next, the module covers the use of Whisper API for voice generation and customization.  

You understand the design principles and architecture of a voice assistant and learn concepts like speech recognition, natural language understanding, dialog management, response generation, etc.

Finally, you deploy your voice assistant using cloud-based, on-premises, and hybrid solutions.

Related: Advantages and Disadvantages of AI

 

8. News Aggregation and Summarization

In this module, you explore the development of a news aggregator application that utilizes text summarization techniques. 

You start by evaluating popular news APIs and setting up API keys for integration. The module covers the implementation of text summarization algorithms using libraries like NLTK or BERT, allowing the generation of concise news summaries. 

In the hands-on project, you work on building both the back-end and front-end of the aggregator using frameworks such as Flask or Django.

You also modify the aggregator’s back-end to enhance user experience and deploy the completed application on a cloud platform.

 

9. Mastering Multimodal GenAI

The final module of the generative AI syllabus focuses on advanced techniques in multimodal generative AI. It covers Early Fusion, Late Fusion, and Hybrid Fusion methods using ChatGPT, DALL-E, and Whisper AI. 

You explore attention mechanisms across these modalities, Progressive GANs, StyleGAN, and Vision-and-Language Transformers (VLT). 

The module also includes temporal modeling for multimodal sequences and meta-learning algorithms.

Then, you learn about knowledge distillation and model compression for optimizing ChatGPT and DALL-E. 

In the final capstone project, you develop a unified AI assistant that integrates text generation, image creation, voice synthesis, and advanced prompting techniques.

Related: How AI will Change the World?

 

Why Should You Join Ivy Pro’s GenAI Course?

You already saw the generative AI syllabus for this course. It’s an 18-week live online program that will make you an IIT-certified AI expert. It covers everything from the basics of AI to advanced topics like machine learning and language models.

The course is taught by experts from IIT Guwahati and top companies, so you will be learning from the best. And, as we said, you will get hands-on experience developing real-world generative AI applications, which is a great way to build a portfolio and stand out in the job market.

And with career support like resume help and interview prep, you will be well-prepared to launch your career in generative AI. So, visit the GenAI course page to learn more about it.

Prateek Agrawal

Prateek Agrawal is the founder and director of Ivy Professional School. He is ranked among the top 20 analytics and data science academicians in India. With over 16 years of experience in consulting and analytics, Prateek has advised more than 50 leading companies worldwide and taught over 7,000 students from top universities like IIT Kharagpur, IIM Kolkata, IIT Delhi, and others.


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