Generative AI and Machine Learning Course from IIT Bhubaneswar with PW Online Degree

Choosing a Generative AI course is not just about learning to work with AI tools. It is about understanding how these technologies are built, how machine learning models process information and how applications such as chatbots, language models and image generators work. For professionals looking to move into AI-focused roles or apply these technologies in their current work, a grounding in programming, mathematics and machine learning is an important starting point.

The Professional Certificate Programme in Generative AI and Machine Learning by IIT Bhubaneswar, offered through PW Online Degree, takes learners from Python and mathematical foundations to advanced topics such as LLMs, prompt engineering, NLP and responsible AI. Over six months, the programme combines 72 hours of live online sessions with practical assignments, case studies and projects, giving learners opportunities to apply concepts as they progress through the curriculum.

What Makes the IIT Bhubaneswar GenAI Programme Stand Out?

The programme combines technical learning with academic support and career-oriented features to help you progress through the course.

• Job-Ready Curriculum: Learn Python, machine learning, Generative AI, LLM applications, NLP and responsible AI through a career-focused curriculum.

• Comprehensive Learning Content: Access subject modules, practical assignments, hands-on projects and additional learning material.

• Career Assistance Workshops: Participate in career-focused workshops to support professional development.

• Experienced Faculty: Learn through sessions led by faculty members from IIT Bhubaneswar.

• Convenient Online Exams: Complete assessments through the programme's online examination format.

• Live and Recorded Lectures: Attend live online sessions and revisit recorded lectures for revision.

• 24/7 Assistance: Access learner support when you need help during the programme.

How the Course Builds Your GenAI Knowledge, One Module at a Time

The curriculum takes you through the essential concepts and techniques used in AI development. You begin with programming and mathematics before moving into Generative AI, machine learning, language processing and practical model development.

1. Programme Induction

Start by understanding the programme's learning objectives, core concepts and the role of Generative AI and machine learning. This introductory module helps you prepare for the technical topics covered in the following sessions.

2. Python Fundamentals

Python is widely used in AI development, from data processing to model building. This module introduces the programming concepts you need before working with machine learning frameworks.

• Python and IDE installation

• Working with Jupyter Notebook

• Identifiers, indentation and comments

• Python data types, operators and strings

• Loops and list comprehension

• Variable scope in functions

3. Mathematical Foundations for Machine Learning

Machine learning models use mathematical concepts to process data, identify patterns and optimise their performance. This module covers the foundations required to understand these techniques.

Key areas include:

• Linear algebra: Vector and matrix dot products, matrix-vector multiplication and singular value decomposition (SVD).

• Probability theory: Random variables, Bayes' theorem and conditional probability.

• Optimisation: Gradient descent, first- and second-order conditions, convex optimisation and KL divergence.

These concepts help you understand how machine learning algorithms represent information, estimate probabilities and improve model performance.

4. Essentials of Generative AI, Prompt Engineering and ChatGPT

Learn what Generative AI can do and how to use it in different business applications. This module introduces prompt engineering and the practical use of ChatGPT.

You will explore:

• Fundamentals of Generative AI

• Prompt engineering principles

• ChatGPT and its applications

• Using GenAI tools for business tasks

• Creating prompts to obtain relevant and useful outputs

The focus is on understanding how prompts influence AI responses and how to use GenAI tools more effectively.

5. Advanced Generative AI: Models and Architectures

Move beyond using AI applications to understanding how generative models work. This module introduces the architectures behind different types of generative systems.

Topics include:

• Introduction to generative models

• Large language model architecture

• Variational autoencoders (VAEs)

• Generative adversarial networks (GANs)

• Attention mechanisms and transformers

6. Building LLM Applications

Learn how to turn your understanding of large language models into functional applications. This module introduces frameworks and techniques for developing, customising and evaluating LLM-powered solutions.

You will cover:

• LangChain and workflow design

• Advanced prompt engineering

• LLM application development

• Fine-tuning and customisation of LLMs

• Benchmarking and evaluating LLM capabilities

7. Machine Learning

Develop an understanding of traditional machine learning methods and how they are used to solve prediction, classification and clustering problems.

The module covers:

• Linear and logistic regression

• Optimisation techniques

• Support vector machines (SVM)

• Decision trees and ensemble methods

• Unsupervised learning and clustering

• Dimensionality reduction using PCA, LDA and t-SNE

• Artificial neural networks

• Perceptrons, multilayer networks and backpropagation

8. Natural Language Processing

Natural Language Processing (NLP) enables machines to process, interpret and generate human language. This module introduces techniques used in text analysis and language modelling.

Topics include:

• Text processing with NLTK and spaCy

• Morphology, stemming and edit distance

• N-gram language modelling, smoothing and perplexity

• Part-of-speech tagging

• Hidden Markov Models and the Viterbi algorithm

• Constituency and dependency parsing

• Context-free and probabilistic context-free grammars

• Text classification using Naive Bayes

• Word embeddings, TF-IDF, Word2Vec and GloVe

9. Generative AI for Image Generation

Explore how generative models can create and process visual content. This module introduces techniques used in AI-based image generation and representation.

You will study:

• Stable Diffusion

• Denoising

• Autoencoders in Generative AI

• Contrastive learning techniques

• Shared embedding spaces

10. Generative AI for Text

Understand how language models have developed and how they generate text. This module explores neural language models, transformer architectures and techniques used to improve LLM performance.

Key topics include:

• Neural language models: CNN, RNN, LSTM, GRU and Seq2Seq architectures.

• Attention mechanisms: Self-attention and transformer architecture.

• Pre-trained models: BERT, GPT and T5.

• Fine-tuning strategies: Task-specific fine-tuning, instruction fine-tuning and preference tuning, including RLHF and PPO.

• Prompting strategies: In-context learning, chain-of-thought prompting, knowledge probing and text generation.

• Augmented LLMs: Retrieval-Augmented Generation (RAG) and tool-augmented LLMs.

11. Responsible AI

Building AI systems also involves understanding the risks associated with their outputs and use. This module introduces important considerations for developing and using AI responsibly.

Topics include:

• Misinformation

• Bias and fairness

• Toxicity

• Security

• Hallucinations

• Strategies to improve the reliability of AI outputs

Turn Concepts Into Working Models with Assignments, Case Studies and Projects

The programme includes practical work that allows you to apply concepts from machine learning, LLM development and Generative AI. Rather than limiting learning to theoretical explanations, you work through implementation tasks involving model training, evaluation and improvement.

Some of the project activities include:

These exercises help you practise different stages of AI development, including model implementation, fine-tuning, performance evaluation and prompt optimisation.

More Than the Core Curriculum: Additional Courses and Learning Support

Alongside the main programme, participants receive access to additional bridge courses of approximately 100 hours. These courses cover related technical and professional skills that can complement your AI learning.

The additional courses include:

• Mastering Data Visualisation with Power BI and MS Excel

• Business Intelligence with Power BI: Advanced Techniques

• Mastering Cloud Technology for Website

• Python Preparatory Course

• Personality Development Programme

• Career Excellence Program

• Professional Course on Communication and Behaviour Skills

• Generative AI Tools Masterclasses

These additional learning opportunities can help you work on skills related to data visualisation, cloud technology, communication and career development alongside the core AI curriculum.

Which Tools and Technologies Will You Explore?

The programme introduces different tools and technology areas used in AI development. These cover programming, LLM applications, machine learning, NLP, computer vision and deployment.

Who Can Apply for the IIT Bhubaneswar GenAI Programme?

The programme is intended for graduates and working professionals who want to build knowledge of Generative AI and machine learning. It may be relevant whether you work in technology, analytics, product development or digital transformation.

Eligibility Criteria

Applicants should meet the following requirements:

• A bachelor's degree with an overall average of 40% or higher.

• A fundamental understanding of mathematics.

• At least one year of work experience is preferred.

• Freshers may also apply.

• Final selection is subject to approval by IIT Bhubaneswar.

If you want to move towards AI-related work, strengthen your technical understanding or explore how GenAI can be applied to business problems, the programme offers an opportunity to study these areas together.

What Certificate Will You Receive Upon Course Completion?

Participants who meet the applicable attendance and evaluation criteria receive a Certificate of Completion issued by IIT Bhubaneswar.

The certificate is awarded subject to the institute's requirements. Meeting the programme's learning and assessment conditions is therefore important for participants who intend to receive the completion certificate.

Career Opportunities After Learning Generative AI and Machine Learning

Knowledge of machine learning and Generative AI can be applied across several technical and business functions. The programme introduces concepts relevant to model development, LLM applications, data analysis, NLP and AI product development.

The skills covered may also be useful in areas such as intelligent automation, predictive analytics, computer vision, language processing and AI application deployment. Career outcomes will depend on your existing qualifications, practical experience, portfolio and the requirements of employers.

Why Choose IIT Bhubaneswar Generative AI and Machine Learning Course through PW Online Degree?

Through PW Online Degree, you can explore professional certificate programmes offered in collaboration with reputed institutions such as IIT Bhubaneswar. PW also provides support beyond course discovery through features such as:

• Course Selection Guidance: Get help understanding programme options and finding a course that matches your interests.

• University and Institute Comparisons: Compare available programmes to make a more informed choice.

• Flexible Payment Support: Explore EMI and financing guidance for eligible programmes.

• Academic Mentoring: Access guidance to support your learning journey.

• Live Doubt-Solving: Get assistance with academic queries through doubt-solving sessions.

• Career Guidance: Access resume-building support, interview preparation, and career mentoring, with placement assistance where applicable.

Building expertise in Generative AI involves understanding the technology behind intelligent systems and learning how to apply it to practical problems. The IIT Bhubaneswar Generative AI and Machine Learning Course brings together Python, machine learning, LLMs, NLP, image generation and responsible AI through live online sessions, assignments and projects. With additional bridge courses and a Certificate of Completion issued by IIT Bhubaneswar for eligible participants, the programme offers learners an opportunity to develop skills across several areas of AI. Through its collaborations with leading institutions, PW Online Degree connects you with specialised programmes that can help you explore emerging technology fields and prepare for evolving career opportunities.