8 Months

Project Based


Seats Left


Last Date to Apply

15th December 2023


Key Features

Industry Oriented Curriculum

In-demand Skills

Live Weekend Sessions

Masterclasses by Industry Experts

Hands-on Projects

Capstone Project

Key Highlights

Master the Machine learning Pipeline: Build, Deploy on AWS Cloud

Develop expertise in core Python for Machine learning and Generative AI

Master Computer Vision & NLP: Advanced Deep Learning Skills

Excel in CV & Natural Language Processing: Advanced Deep Learning

Master ChatGPT & Dall-E: Advanced Model Training

Understand LIME & SHAP: Models with Interpretability

According to a report by Gartner, the year 2025 will see 2 millionnew jobs generated by AI and ML.

India is among the top three talent markets, producing 16% of the world’s AI talent pool. Source:

Step into the world of ML & AI

Experience best-in-class content developed by leading faculty & industry leaders.


Aspiring Data Scientists

Software Engineers & Developers

Technology Enthusiasts

Business Professionals & Entrepreneurs

College Students

Researchers & Academicians

Tools You will work with



  • When you complete a course with us, you become the most desirable candidate in the field of Machine Learning & Generative AI
  • Note : Sample Certificate



Machine Learning Engineer


Data Scientist


Deep Learning Engineer


AI Researcher


Computer Vision Engineer


AI Solution Architect


Learn from India's leading ML & AI faculty and industry leaders


Dr. Lipika Dey

Working as Chief Scientist at Tata Consultancy Services (TCS). Currently heading research in the theme of Economic and Financial Intelligence. Areas of interest are Natural Language Processing, Artificial Intelligence applications, Machine learning, and analytics of multi-structured data. Has been awarded the Fellowship of Indian National Academy of Engineering (FNAE) in 2021.


Dr. Tirthankar Dasgupta

Working as scientist at TCS Research working in the Decision Intelligence group, Kolkata. Holds a Ph.D. in computer science from Indian Institute of Technology, Kharagpur. Research interests span Artificial Intelligence, Natural Language Processing, Deep Learning and Computational Psycholinguistics.


Dr. Sakshi Babbar

Enterprising professional with over 9 years of rich experience as a subject matter expert in Machine Learning and Data Science. Acquires extensive knowledge in working with data, developing and deploying machine learning models. She is a certified AWS Machine learning specialist with expertise in AWS Sagemaker.


Debashis Roy

Working as Technical Lead and Product Manager for conceptualizing and implementation of Hands-On environment on iON Cloud platform for Higher Education Learning products. Worked as SME for Artificial Intelligence, Deep Learning, Data Science, Big Data Analytics, Cloud Computing and Architecture, DevOps, Blockchain, etc.


Dr. Himdweep Walia

Working as SME and Product Manager having end-to-end ownership of learning products in the AI/ ML domain for Higher Education Learning products. Having 18+ years of experience. Ph. D. in Natural Language Processing Research interest includes Artificial Intelligence, Machine Learning, NLP & Vision Intelligence.


Mr. Naveen Bhansali

Working as scientist at TCS Research working in the Decision Intelligence group, Kolkata. Holds a Ph.D. in computer science from Indian Institute of Technology, Kharagpur. Research interests span Artificial Intelligence, Natural Language Processing, Deep Learning and Computational Psycholinguistics.


Mr. Pranav Shastri

He has teaching experience of 11 years in training. He has conducted successful training sessions in data science and deep learninig at Indian Naval Institute and Bombay Stock Exchange Institute.


By the end of this module, learners will understand the fundamental concepts of machine learning, including supervised and unsupervised learning techniques. They will be able to interpret machine learning algorithms and their applications,

Upon completion of this module, participants will possess the skills to efficiently collect, clean, and preprocess large datasets using popular tools such as Apache Spark and TensorFlow Data Validation. They will apply various data engineering techniques, including feature engineering and dimensionality reduction, to ensure data quality and optimize model performance. Additionally, students will work on real-life projects, addressing specific industry problems and utilizing machine learning and deep learning techniques to extract valuable insights from the data.

After completing this module, students will be capable of building and evaluating machine learning models using a variety of algorithms, such as decision trees, random forests, and gradient boosting. They will gain hands-on experience with libraries like scikit-learn and XGBoost to implement model training and evaluation procedures. Furthermore, learners will apply their knowledge to real-life projects, tackling industry-specific challenges and employing advanced machine learning techniques to derive meaningful predictions and recommendations.

At the end of this module, learners will have a comprehensive understanding of deep learning architectures and techniques, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and transformers. They will gain practical experience with popular frameworks such as TensorFlow and PyTorch, implementing and fine-tuning deep neural networks for tasks like image classification, natural language processing, and sequence generation. Students will also engage in real-life projects, using deep learning techniques to address complex real-world problems and deliver innovative solutions.

Upon completion of this module, participants will be adept at using Amazon Web Services (AWS) for deploying and managing machine learning applications. They will gain hands-on experience with AWS services like Amazon SageMaker and Amazon Recognition, mastering the end-to-end process of building scalable machine learning pipelines on the cloud. Learners will work on real-life projects, leveraging AWS infrastructure to tackle industry-specific challenges and develop production-ready machine learning systems.

By the end of this module, students will master the development and deployment of generative AI models, including GANs, VAEs, and transformers, using popular frameworks like TensorFlow and PyTorch. They will gain hands-on experience with cutting-edge tools such as ChatGPT and Dell-E. Working on real-life projects, students will apply generative AI techniques to create realistic images, generate coherent text, and compose unique music pieces at the mid journey of their learning.

Project Topic: Indian Regional Language Translator

Business Domain: NLP & Translation

A regional language translator is a software application or service that allows users to translate text or speech from one regional language to another, typically between languages that are not commonly used outside of a specific region or country. Regional language translators are designed to address the language barriers that exist between different communities and languages within a region. Regional language translators use a variety of techniques to translate text, including statistical machine translation, rule-based translation, and neural machine translation. These techniques involve analyzing the structure and meaning of the source language and using that information to generate a translation in the target language.


  • Apply supervised and unsupervised learning techniques to solve real-world problems.
  • Implement deep learning models, including CNNs and RNNs, for computer vision and sequential data analysis.
  • Use generative AI models, such as VAEs and GANs, for image and text generation.
  • Apply computer vision techniques using the OpenCV library for image classification and object detection.
  • Build end-to-end machine learning pipelines for data preprocessing, model training, and deployment
  • Use AWS services, including Amazon SageMaker, for machine learning on the cloud.
  • Understand ethical implications and challenges related to bias, privacy, and transparency in machine learning and generative AI.


Project Topic: Integrated Agriculture Analysis

Business Domain: Agriculture and Prediction System

Integrated agriculture analysis is the process of combining various data sources and analytical techniques to provide insights into the performance and sustainability of agricultural systems. This approach integrates data from a range of sources, including weather patterns, soil characteristics, crop yields, and market trends, to provide a comprehensive understanding of agricultural systems.

Project Topic: Smart Retail Analytics: Supermarket Chain

Business Domain: Retail and FMCG

The project should support analytical activities related to sales of products along with customer requirements, availability, and procurement of products. This should include features related to KPI identification, EDA, association analysis of items, smart visualizations using interactive reports and dashboards.

Project Topic: Cyber Threat Analysis on Android Apps

Business Domain: Cyber Security

Cyber threat analysis on Android apps involves using machine learning algorithms to identify and analyse potential security threats in Android apps. With millions of apps available on the Google Play Store, it is important to ensure that these apps do not contain malicious code or vulnerabilities that can be exploited by attackers. To perform cyber threat analysis on Android apps using machine learning, the first step is to collect a dataset of known threats and non-threats. This dataset can be used to train a machine learning model to identify patterns and anomalies that may indicate the presence of a threat.

Project Topic: Interactive Behavior Analysis in discussions

Business Domain: Human Behavior Analytics

This project would focus to analyze interactive human behavior under different situations and discussions like presentations, interviews etc. to understand the emotional stability under different conditions. The system should comprise of deep learning models that can analyze patterns and behaviors from bot based textual interactions as well as from facial expressions and other behavioral patterns captured through system camera while interacting. The analyzer module should be capable of comparing emotions from both text and images and deduce appropriate results.

Project Topic: Intelligent Property Analyzer using MLOPs

Business Domain: Real Estate Market

To develop a ML-powered automated system using Machine Learning operations on Cloud to accomplish tasks to predict the approximate price of a housing property based on multiple factors related to the property. This should comprise of MLOps and pipeline-based Data Wrangler, feature store, detect imbalance and bias as data would be transferred dynamically and the model should be capable of considering latest data inputs for prediction.

Project Topic: People’s behavior analysis in Chat Message

Business Domain: Social Media Analysis

People's behavior analysis in chat messages involves using machine learning algorithms to analyze the language used in chat messages to gain insights into the behavior and personality of individuals. For example, sentiment analysis can be used to identify whether a person's messages are generally positive, negative, or neutral in tone. Word choice analysis can be used to identify the types of words and phrases that a person uses frequently, which can provide insights into their interests and personality.

Program Fee

INR 120,000 1,00,000 + GST

Frequently Asked Questions

Classified as one of the upcoming technologies, Aritifical Intelligence or AI is the ability of a robot or a machine, to perform complex tasks, without human input. AI can further be divided into four categories, namely, Reactive Machines, Limited Memory, Theory of Mind and Self-Awareness. A few areas where AI can be efficiently implemented include Automation, Machine Learning, Machine Vision, Robotics, Self-Driving Cars and more.

AI Engineers tend to play a vital role in building an infrastructure around AI. Apart from defining problems to be solved and chalking out strategies, AI Engineers are also required to use programming algorithms to deploy, test and build AI models. In order to be a succesful AI Engineer, an indivdual must be well-versed in several programing languages like Scala, TypeScript, C++, R, Python Java. To add to the tally, the engineers hould also display expertise in Linear Algebra, Calculus, Statistics and Probability. This further helps the AI Engineers to have a better understanding of AI models including Gaussian Mixture Models, Hidden Markov, Linear Discriminant Analysisand Naïve Bayes.

A course in Artificial Intelligence course equips indivduals to become an AI specialist by providing them with with an overview of AI technology and processes. Educational qualification from recognised institutes like Amity University and Future Academy also tend to go a long way, in helping aspirants bag jobs in reputed organizations across the globe as an AI specilist! The AI spcialists also need to shoulder several responsbilities including carrying out staistical analysis on the systems created, monitoring pre-existing systems, developing the infrastructure for data transformation and data ingestion and converting Machine Learning Models to APIs.

Professionals with through knowledge of AI models and the evolving market trends can make a flourishing career in the field of AI. A few job opportunities that an AI Engineer or a specialist can apply for include Machine Learning Engineer, Computer Vision Engineer, Research ML/AI, Business Intelligence Developer, Big Data, Architect, NLP Engineer and more.

Aspiring candidates should have completed class 12th from any recognized Education Board.

The duration of this course is 8 months. You will have access to the course for 12 months

You should opt for the Certificate in Machine Learning and Generative AI for hands-on learning in collaboration with industry partner TCS ION including real-world mini-projects and a capstone project. The program's curriculum has been meticulously designed by TCS ION industry experts & expert Amity University Online faculty to ensure that you acquire job-ready skills in the rapidly evolving AI landscape.

The Certificate in Machine Learning and Generative AI will help you to build a solid foundation in Statistics, Machine Learning, and AI,and acquire problem-solving skills so that you can solve enterprise-level problems and transition to a Senior Data Science or Machine Learning role.

he application process is completely online and hassle free: Following are the key steps to enroll in the Certificate in Machine Learning and Generative AI:
STEP-1: Click 'Apply Now', fill in your details and submit your aplication for the Certificate in Machine Learning and Generative AI.
STEP 2: Claim your seat by paying the Registration Amount (followed by paying the balance amount) OR paying the Full Amount. You may also avail assistance from our loan partners.

Yes, we offer flexible financing options, including EMI plans, to make it convenient for you to choose the payment method that suits your budget and preferences. You can also opt for self-payment.