What Is the Executive Post Graduate Certificate in Applied AI & Machine Learning?
Key Highlights: Executive Post Graduate Certificate in Applied AI & Machine Learning
What Is Applied AI, and How Does This Programme Teach It?
Applied AI is more about creating and implementing AI powered systems and machines which helps to tackle real life issues. It primarily involves developing and using AI techniques in the form of a concrete problem rather than theoretical algorithms studies.
The IIT Kharagpur applied AI and machine learning course builds on this approach by gradually exposing learners to the basics of math and programming, to machine learning and deep learning, to NLP, Generative AI, RAG, Agentic AI, deployment, and MLOps.
For example, someone could make an AI system that is able to analyze information from a manufacturing process, collect the operational documents which are related, or may be support a business workflow. The capstone helps the learner to apply their learning to a selected real life problem in domains such as healthcare, BFSI or manufacturing.
Why Choose the IIT Kharagpur Executive Post Graduate Certificate in Applied AI & Machine Learning?
The building of an AI model is only one part, the real picture is when it comes for launching. Also, there are data preparation, model evaluation, connecting AI systems to applications, managing cost and latency, as well as monitoring the deployed systems in a way that you don't forget about them.
The programme covers these areas through:
Faculty-led learning: You will undergo online classes that will be led by the faculty members of the Indian Institute of Technology, Kharagpur.
Foundational preparation: In the first step, you will be acquainted with foundational programming languages, such as Python, SQL, and other subjects including statistics, linear algebra, probability, and calculus, via a Foundations Bridge.
Full AI development path: In the AI roadmap, you will go through steps from machine learning, deep learning, NLP, Generative AI, RAG, and Agentic AI to deployment.
Guided projects: You will put all of your learning to practice through real-life AI applications on a module-by-module basis.
Deployment focus: You will not only focus on technical aspects but also how to balance cost, reliability and monitor and meet various deployment requirements.
Capstone project: In this you get to build an AI system to tackle a problem in Healthcare, BFSI, Manufacturing or a related field.
What Will You Learn in the Executive Post Graduate Certificate in Applied AI & Machine Learning?
The IIT Kharagpur Applied AI & Machine Learning syllabus begins with a foundational Bridge and continues through six core modules. The syllabus consists of these modules:
AI Foundations Bridge
Duration: Before the core programme
The Foundations Bridge helps learners who are from different backgrounds and prepare them for the core modules. It helps them by covering these topics:
Topics Covered:
Python programming
SQL
Statistics
Linear algebra
Probability
Calculus
Skills Acquired:
Building a foundation in programming and data handling
Working with essential mathematical concepts
Preparing for machine learning and deep learning
Identifying and addressing foundational knowledge gaps
Module 1: Machine Learning Foundations
This module is the beginning of the fundamentals of machine learning. The topics covered in this module are:
Topics Covered:
Machine learning foundations
End-to-end ML system development
Data preparation and model training
Model evaluation and deployment
Skills Acquired:
Preparing data for machine learning
Training and evaluating a model
Connecting model development with deployment
Demonstrating a complete ML workflow
Module 2: Deep Learning & Computer Vision
This module covers deep learning and computer vision. The topics covered in the module are:
Topics Covered:
Deep learning
Computer vision
Vision-based and sequence-based models
Model training, evaluation, and deployment
Skills Acquired:
Training a deep learning model
Evaluating and improving model performance
Preparing a model for deployment as a usable service
Demonstrating a deployed model
Module 3: NLP, Transformers & Speech AI
This module covers natural language processing, transformer models, and speech AI.
Topics Covered:
Natural language processing
Transformer models
Speech AI
Skills Acquired:
Applying NLP techniques to process and analyse text
Understanding transformer architectures and their use in language tasks
Working with language models for text-based applications
Understanding speech AI concepts and their applications
Identifying suitable NLP, transformer, and speech AI approaches for different problems
Module 4: Generative AI & LLM Applications
This module covers Generative AI and applications built with large language models. The topics covered in this module are:
Topics Covered:
Generative AI
Large language model applications
Prompting
Lightweight fine-tuning
Agent-based workflows
Skills Acquired:
Building a Generative AI application
Applying prompting techniques
Understanding lightweight LLM adaptation
Connecting language models with application workflows
Module 5: RAG Systems & LLM Orchestration
This module focuses on retrieval-augmented generation and LLM orchestration. The topics covered in this module are:
Topics Covered:
Retrieval-Augmented Generation
Vector search
LLM orchestration
Skills Acquired:
Building a retrieval-based AI system
Connecting information retrieval with generated responses
Working with vector search and orchestration concepts
Demonstrating a RAG application
Module 6: Agentic AI, MLOps, Deployment & AI Governance
This module brings together Agentic AI, model operations, deployment, and AI governance.
Topics Covered:
Agentic AI
MLOps
AI deployment
AI governance
Skills Acquired:
Developing AI applications that use agent-based workflows
Understanding deployment and operational requirements
Working with monitoring and versioning concepts
Considering governance and responsible AI use
What Will You Build During the IIT Kharagpur AI course?
Each project in this IIT AI course focuses on a different part of AI development, from model building to retrieval, application development, and deployment. The projects covered in the programme are:
1. End-to-End Machine Learning System
Create a system that is capable of preparing data, developing models, testing them and even deploying them. This could be an example of the typical machine learning workflow steps.
Skills demonstrated: You will work through the major parts of an ML workflow and will successfully develop a model and also deployed it.
2. Deployed Deep Learning Model
Create and optimise a deep learning model, then release it as an accessible service that can be used after being trained.
Skills demonstrated: You have been able to create a deep learning model and also have been capable and willing of exposing the model beyond the training situation.
3. Production-Grade RAG System
Using vector search & orchestration, create a retrieval-augmented system with a focus on production.
Skills demonstrated: Integrating information search with language model responses and designing a RAG-based application.
4. GenAI and Agentic AI Application with LLM Adaptation
Design a Generative AI application that includes prompting, lightweight fine-tuning and agent-based workflows.
Skills demonstrated: Applying LLM adaptation methods and linking language models with application flows.
5. Deployed AI API
Build an AI service that is deployed and accessible via APIs after getting a container. Outcome includes monitoring, versioning and ensuring the service is ready for real-world traffic.
Skills demonstrated: Preparing an AI service for deployment and understanding production monitoring requirements.
6. Industry Capstone Project
You are supposed to identify an authentic problem within Healthcare, BFSI, Manufacturing, or any other industry and go about solving it from problem definition through architecture and implementation.
Skills demonstrated: Problem-solving through the integration of AI development.
Tools and Technologies Covered in the Executive Post Graduate Certificate in Applied AI & Machine Learning
The IIT Kharagpur AI course covers these tools and technologies along with the core modules:
1. Programming and Data Foundations
Python: Programming for AI and machine learning.
SQL: Working with structured data.
Statistics, linear algebra, probability, and calculus: Mathematical foundations for AI.
2. Generative AI and Retrieval
Large language model applications
Generative AI and prompting
Lightweight LLM fine-tuning
Retrieval-Augmented Generation
Vector search and LLM orchestration
3. Deployment and MLOps
The programme covers deployment and operation of AI applications, including:
AI APIs and containerised services
Monitoring and versioning
MLOps
Agentic AI and AI governance
Who Should Enrol in the Executive Post Graduate Certificate in Applied AI & Machine Learning?
This is the IIT AI course for working professionals who have a technical or analytical background. This programme fits you if you are:
Software Engineers
If your focus is APIs, software services, or developing applications this IIT AI course teaches you how to implement machine learning and deep learning, use Generative AI, RAGs and AI deployment in production.
AI and Machine Learning Engineers
This applied AI machine learning course for you opens a broader range of NLP, language models, Agentic AI, MLOps and deployment. It is ideal if you work with models or ML pipelines.
Data and Analytical Professionals
Before jumping into AI you have to learn certain things and if data and analysis are your core functions the bridge in this IIT Kharagpur AI course will provide you with knowledge of programming, SQL, statistics, linear algebra, probability, and calculus.
Engineers in Healthcare, BFSI, and Manufacturing
Since AI in these industries is used in day-to-day operations, a capstone in this applied AI course gives you the opportunity to practice what you've learned and solve real problems in your field.
Pre-Sales and Solutions Professionals
If you do product demos, design solutions or present how to deploy systems, the part of this IIT AI ML course for working professionals that deals with AI development and deployment will give you more confidence in knowing how AI apps work.
Who May Not Find This Programme Suitable?
For learners who have zero experience with programming and want only a totally non-technical overview of AI, this IIT Kharagpur AI course may not be the right program. Besides, it is not presented as a research degree or as a leadership-only programme. Learners are advised to have a minimum basic knowledge of programming and mathematics.
Eligibility Criteria for the Executive Post Graduate Certificate in Applied AI & Machine Learning
The eligibility criteria for this IIT Kharagpur AI course are:
Graduation with a minimum of 50% marks
B.Tech/M.Tech or B.E/M.E, preferably in Computer Science, Information Technology, Artificial Intelligence, or Electronics and Communication Engineering
B.Sc/M.Sc in Computer Science, Mathematics, or Statistics
MCA or BCA
Candidates from other disciplines must have at least two years of experience in the technology field
Prerequisites:
Before joining, candidates should have:
Basic programming logic
Familiarity with any programming language
Comfort with foundational mathematics, including algebra, probability, and statistics
IIT Kharagpur Executive Post Graduate Certificate in Applied AI & Machine Learning Course Fees Structure
The IIT Kharagpur AI course fees structure is as follows:
How to Apply for the Executive Post Graduate Certificate in Applied AI & Machine Learning?
To apply for this IIT AI course, you have to follow these steps:
Complete the application: You need to complete the application form.
Receive a provisional offer: Shortlisting will be done and you will get a provisional offer letter.
Block your seat: Deposit the seat blocking amount along with the necessary documents.
Complete enrolment: On completion of the document verification process, pay the balance amount.