PG Diploma M.Tech. in Artificial Intelligence - RACE
India’s First Research Driven
M.Tech. in
Artificial Intelligence
Offered in Association with
AWS Academy and Microsoft Azure
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India’s First Research Driven
M.Tech. in
Artificial Intelligence
Offered in Association with AWS Academy and Microsoft Azure

Start Date

September 2024


2 Years


Approved by AICTE

Program Fee

INR 5.2 Lakhs


Average Salary


Average Hike


Median Salary


Median Hike


Hiring Partners

Achieve your career goals

Santosh Shirol

Santosh Shirol
M.Tech in Artificial Intelligence, 2023
Senior Developer L3
Senior Member of Techincal Staff QA
SAP Labs India Pvt. Ltd.

Sabyasachi Sengupta

Sabyasachi Sengupta
M.Tech in Artificial Intelligence
Associate Manager
Principal Senior Engineering Manager

Praveena Vallivel

Praveena Vallivel
M.Tech in Artificial Intelligence, 2023
Design Lead
Director Data Science
Ernst & Young

Soumya Shrivastava

Soumya Shrivastava
M.Tech in Artificial Intelligence, 2023
Engineering Manager
Developer Associate
MC Millan

Shivpriya V

Shivpriya V
M.Tech in Artificial Intelligence, 2023
Delivery Manager

Rajanna K

Rajanna K
M.Tech in Artificial Intelligence, 2022
Senior Staff Manager
Techincal Lead Testing

Kathiresan R S

Kathiresan R S
M.Tech in Artificial Intelligence, 2023
System Specialist
Solution Architect

Bharadwaz Sripada

Bharadwaz Sripada
M.Tech in Artificial Intelligence, 2023
Senior Analyst
Senior Program Manager
LM Wind Power

Power Up Your Career with Artificial Intelligence

By engaging in the module sessions and real-time projects, the participants will get exposure to full-stack AI skills.
Modules + Capstone Projects + Real time Projects = Full Stack AI Skills

Data Engineering

Infrastructure Configuration

Resource Management

Data Collection and Management

Servers/Cloud Automation


Data Science

Data Processing

Feature Engineering

Sampling and Validation

Machine Learning

Deep Learning


AI/ML Operations


Performance Monitoring

Resource Optimisation



Artifical Intelligence Product/Project Management Life Cycle and Process

Program feature

Build a lucrative career path in Artificial Intelligence with the M.Tech. in Artificial Intelligence program. This is a 100% outcome-driven and skill-based program exclusively designed for working professionals in mid and senior positions to accomplish a smooth career transition into the highly rewarding AI field. The 24 month program is recognised by UGC and focuses on hands-on learning using proprietary or open software tools in the AI market today.

Industry Thought Leaders
as Mentors

Our industry mentors have decades of experience in the industry and hence participants will receive hands-on experience with various analytics applications to solve real-time business issues.

LMS with the best in
Class Resources

An integrated Learning Management System (LMS) that provides 24/7 access support to aspirants with in-class reading support, interactive resources, real case database datasets, recordings of sessions, and other resources.

Industry Grade

Real-time case studies with labs and simulations provide hands-on learning opportunities that help participants gain a thorough understanding of the subject and how it is applied in the real world. 


The lateral placement services such as career guidance, resume building, and mock interviews with industry mentors and alumni help our participants to transition their careers and bag lucrative offers.

Why Artificial Intelligence with RACE?

  1. Develop Full-Stack AI skills
    This unique program will help learners design end-to-end AI solutions and data-driven processes and systems. The program emphasizes building technical solutions with machine learning and/or deep learning and deploying and monitoring them on-premise/cloud.
  2. Three Global Certifications from Microsoft Azure and AWS Academy
    The participants will get access to two globally renowned cloud platforms, Microsoft Azure and AWS Cloud. They will have unlimited access to our academic partners’ ecosystem, including Cloud labs access, course materials, partners’ LMS, placement services, mentoring sessions, and three global certifications.
  3. Building Techno-Functional Expertise
    A well-balanced program curriculum ensures that the learner builds deep technical and functional expertise in building Machine Learning/Deep Learning-based applications in all enterprise functions, new projects, and product developments based on business/social/research challenges, thus making a very strong resume with hands-on skills which are a rarity today.
  4. Hands-on Learning with Focus on Research and Innovation
    During this two-year M.Sc. in AI program, learners will get to work on 15 plus mini-projects, four plus full-scale projects, and research publication(s). These projects are mentored by industry thought leaders and hence career transformational. The projects range from business use cases to cutting-edge deep-learning product development.
  5. Lateral Placement with Career Guidance & Support
    A vast network of 50 plus industry mentors, 100 plus marquee organizations as placement partners, 1000 plus strong alumni network ensures a successful career transition of learners into AI Architects during the program. The lateral placement process is uniquely designed with one-on-one career guidance and mentoring sessions, resume building support, special training, and mock interviews that support learners to be placed nationally and internationally with an average increase in salary of 50 to 200%.

Admissions closes on 21st Sept. 2024

Curriculum Highlights

  • 72 Credits
  • 4 Semesters
  • 19 Modules
  • 10+ Mini Projects
  • 2 Capstone Projects with Industry Mentorship
  • 3 Global Certifications
  • 1 Research Journal Publication

Semester- I

In this module, the participants will learn the building blocks of intelligent systems. They will explore the best practices to harness the power of complex data structures like lists, sets, dictionaries, and tuples to store the data. They will also learn to design custom functions, write scripts, handle errors, and create and generate basic AI algorithms. They will be able to embed reasoning and thinking into programming. After completing this module, the participants will be able to manipulate the functions, source codes, and debug the Python programs, write fluent Python reasoning-based functions, and integrate programs and functions written in different languages/tools.

Tools: Python

This course provides knowledge and skills for understanding Linear Algebra fundamentals and applications in Machine Learning. Participants will work on a few in-classroom projects to get the firsthand experience of their skills. The learners will work on advanced matrix operations and supervised and unsupervised algorithms using linear algebra. Hands-on projects on customer segmentation, dimension reduction, and topic modeling are the highlights of the module.

Tools: Python

The course on Data Processing for AI will provide knowledge and skills related to SQL, for handling structured/tabular data. Participants will work with structured and unstructured data and its types. They will learn about collecting and accessing text data from different sources, implementing text cleaning, preprocessing and feature engineering in NLP, and advanced methods of feature engineering. At the end of the course, the participant will be equipped with knowledge, skill, and experience to handle structured, i.e., tabular data and unstructured data such as text, image, video, etc., in AI and Data Science Projects.

Tools: SQL, NoSQL, Python

This module aims to provide a strong foundation in applying statistical concepts and methods in real-world situations and domains related to analytics. The course intends to provide them with experience in communicating the results to non-statistical/business stakeholders and present their cases with appropriate business relevance. They will learn univariate, bivariate, and multivariate statistical techniques, setting and testing hypotheses, sampling, probability, and building statistical models.

Tools: Python, R

This module combines concepts, tools, and practical workshops to familiarize and build expertise in Machine Learning algorithms and model building processes. Practical skills in building supervised and unsupervised algorithms through industry-relevant case studies and datasets are the focus. The topics covered include approaches to ML, Data preparation for ML, Supervised learning, Linear models, Neural networks, Perceptron, Linear SVM, Non-linear models, Multi-layer perceptron, Decision trees, Random forests, Support vector machines, Bayesian modeling, Independent models, Naïve Bayesian modeling, and more.

Tools: Python

Semester- II

The objective of this module is to make the participants implement and apply state-of-the-art deep learning models in real-world problems. The participants will get in-depth understanding and hands-on exposure to applying deep learning methods to solve a variety of computer vision-based problems. The labs include building a deep neural network for a given problem, hyper-parameter tuning, and optimization to make sure it avoids overfitting, building a time sequence-based neural networks and solving the problems of forecasting, building CNN for image processing tasks, learn how and when to use Autoencoders and familiarize with the latest advances in deep learning.

Tools: Python

This course provides an introduction to some of the foundational ideas on which modern reinforcement learning is built, including Markov decision processes, value functions, Monte Carlo estimation, dynamic programming, temporal difference learning, eligibility traces, and function approximation. This course will develop an intuitive understanding of these concepts (taking the agent’s perspective) while also focusing on the mathematical theory of reinforcement learning. Programming assignments and projects will require implementing and testing complete decision-making systems.

Tools: Python, OpenAI Gym, Keras, Jupyter Toolkit

The objective of this course is to develop the skills to gain a basic understanding of neural network theory and fuzzy logic theory and introduce students to artificial neural networks and fuzzy logic theory, and introduce from an engineering perspective. The learner will work on fuzzy logic, fuzzy inference systems, probability theories, Bayesian probability-prior, conditional and posterior probabilities, Bayesian network, Gibbs sampler, inference in graphical models, reasoning with uncertainty, unsupervised learning – expectation maximization, supervised learning – Naïve Bayes, Full Bayes, genetic algorithms, genetic programming, and more.

Tools: Python, OpenAI Gym, Keras, Jupyter Toolkit

This course will focus on building end-to-end lifecycle of AI applications, from deployment to ongoing maintenance. The participants will learn best practices in integrating AI models into production environments, optimizing performance, and ensuring system reliability. The course will cover key aspects such as version control, scalability, and automated monitoring. Tools used include Docker for containerization, Kubernetes for orchestrating containerized applications, TensorFlow for deploying AI models, and Jenkins for continuous integration and continuous deployment (CI/CD). This course equips learners with the skills needed to manage robust, scalable, and efficient AI systems in real-world settings.

Tools: Python/Google Collab, AWS/Azure

The first-year Artificial Intelligence program will culminate in designing, preparing, and presenting a real-time capstone project on a live technical/business challenge. Each of the participants gets to work with a senior industry mentor for guidance spanning six weeks. The final certification is strictly based on the successful completion and submission of the capstone project with a favorable assessment from the panel of industry mentors. The objective is to develop your managerial and consulting capabilities by applying the lessons learned in the program to real-life AI challenges.

Tools: Full-stack

Semester- III

This course will explore the principles and techniques used in real-world computer vision systems and the research and development of new systems. The module will cover image processing fundamentals, basics and applications of digital image processing, intensity transformations and color image processing, image filtering, and advanced image processing methods, spatial image filtering, image features, feature matching, texture matching, image segmentation, clustering images, classification of images, video analytics, and more. At the end of this course, the participants will understand and master essential knowledge, theories, and methods in image processing and computer vision.

Tools: Python, Tensorflow, Keras

This course provides a unique opportunity for you to learn key components of text mining and analytics aided by real-world datasets and the text mining toolkit. Hands-on experience in core text mining techniques including text preprocessing, sentiment analysis, and topic modeling help the learners to be competent data scientists. After completing this course, participants will know all the basic concepts of natural language processing to be applied with text data and hands-on exposure to implementing NLP models to find insights from the text data.

Tools: Python

The objective of this course is to make the participants able to develop and use speech analytics tools that can indicate why the customers are calling, provide real-time analytics for agents, and even monitor conversions. At the end of this course, participants will be familiar with speech analytics methods and applications, along with hands-on knowledge of how to develop and use speech analytics tools and apply speech analytics methods to address real-world problems. The labs will include elements of speech systems, specular reflection, specularity, speech Input device, speech analysis, speech parameterization, speech processing, speech production, speech recognition, speech spectral envelope, speech synthesis, speech system, text-to-speech, and speech-to-text modeling, and more.

Tools: Python

This course focuses on the architecture, tools, and techniques used to collect, store, process, and analyze large-scale data. Learners will learn to design and implement data pipelines, optimize data workflows, and ensure data quality and integrity. The course covers distributed computing, data warehousing, and real-time processing, along with advanced analytics and machine learning. Key areas include Hadoop for distributed storage, Spark for large-scale data processing, Kafka for real-time data streaming, SQL for database management, and Python for data analysis. This course prepares learners to build robust big data solutions and derive actionable insights from complex datasets.

Tools: Hadoop, Spark, Kafka, NoSQL, SQL, Python

This course explores the creation of models capable of generating new, original content such as text, images, and music. Participants will learn about the principles of generative models, including Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and transformers. The course covers techniques for training and fine-tuning these models, as well as ethical considerations and real-world applications. Key tools include TensorFlow and PyTorch for building and training models, GPT for text generation, DALL-E for image creation, and Jupyter Notebooks for experimentation and visualization. This course equips the learners with the skills to develop and apply cutting-edge generative AI technologies in various domains.

Tools: TensorFlow, PyTorch, GPT, Python

The second-year AI program will culminate in designing, preparing, and presenting/publishing a real-time capstone project on a live technical/business challenge in AI. The scope and business applications of the project need to be larger than the first-year project. Designing and implementing, deploying, and demonstrating an end-to-end AI project with a reasonable monetary benefit need to be built. The program office will support with mentoring and report writing. The evaluation is based on viva-voce by an industry panel of experts.

Tools: Full Stack

Semester- IV

This module deals with designing and implementing a data science solution on Microsoft Azure. The participants will learn to create and manage Azure and Data Bricks workspace, run and monitor models, automated MLs and tune hyper-parameters, and deploy and operationalize machine-learning solutions in the Azure cloud environment. The participants will go through the DP-100 to qualify as Microsoft Certified Azure Data Scientists.

Tools: Microsoft Azure Machine Learning Studio, Databricks

This is a Microsoft Azure-based module with certification. The learners will be able to design and deploy AI systems with Azure through this course. They will plan and manage an azure cognitive services solution, implement computer vision solutions, NLP solutions, knowledge solutions, and conversational AI solutions. After completing the certification exam, they will be designated as Azure AI Engineer Associate.

Tools: Microsoft Azure Cognitive Services, Custom Visions Services, Video Indexer, Language Understanding Service (LUIS), QnA Maker, etc.

This module credits can be earned by writing and publishing a research paper on the capstone project done in the earlier module. The participant needs to publish or present the paper in a peer-reviewed journal or reputed international conference. The participants will learn skills in research paper writing and publishing/presenting. The program office will provide extensive support on publications, which includes access to research articles and repositories, five-plus paid databases, writing boot camps, mentoring, publication, and patenting support.

Tools: Python.

Google Reviews

06:17 17 Jan 24
Exceptional RACE cybersecurity course! Engaging content and hands-on exercises provide practical skills for navigating the digital landscape. Highly recommend to anyone looking to fortify their cybersecurity knowledge."
11:30 12 Dec 23
"REVA's Masters program immersed me in a dynamic learning environment, fostering a holistic approach ."Collaborative projects and interactive sessions honed my teamwork and communication skills.""The supportive faculty and cutting-edge resources created a transformative academic experience.""Overall, REVA's Masters program not only enriched my expertise but also empowered me for future challenges."
04:57 11 Nov 23
It was an exciting journey and RACE has helped me to boost my career to next level.
poornima poornimapoornima poornima
04:46 11 Nov 23
REVA RACE offers industry-driven curriculum which is delivered by industry experts. RACE team is very supportive and the program helped me to upskill in my career path.
Patnana SayesuPatnana Sayesu
09:36 10 Nov 23
My name is Patnana Sayesu, and I'd want to tell you about my great experience at RACE Reva University. During my M.Tech in Cyber Security, I gained essential hands-on experience and polished fundamental domain skills with the help of industrial expert mentors. The program's emphasis on real-world projects and training from experienced professionals prepared me to face real-world industry issues.Notably, the support I received from dedicated mentors and program office coordinators was critical to my success. I am grateful for the opportunity to gain global certificates and, as proof of the program's effectiveness, to secure two public-sector positions while continuing my studies.I would want to express my heartfelt gratitude to all mentors, trainers, and program office coordinators who have helped me reach both short and long-term professional goals.Thank you!Patnana Sayesu
Amit LambiAmit Lambi
11:45 04 Nov 23
I highly recommend REVA Academy for Corporate Excellence (RACE) for anyone looking to advance their professional skills. The courses offered are top-notch and cover a wide range of topics, from A.I/Data Analytics to Cyber Security/Cloud Computing. The instructors are experts in their respective fields and provide valuable insights and real-world examples. The online platform is easy to use and the materials are well-organized. I particularly appreciated the interactive nature of the classes and the opportunity to network with other professionals. Overall, RACE is an excellent investment in professional growth.
Anand MohanAnand Mohan
13:56 09 Oct 23
In 2019, I was seeking an MBA program. I researched numerous Tier-2 executive MBA programs to make sure I could make the most of the money I had spent on the program. However, I was dismayed to find from numerous responders that part-time MBA programs at Tier-2 B-schools are not even close to matching their full-time equivalents.RACE was a really unique experience. The executive MBA ended up educating you far more than a full-time course would have. Top-notch mentors from major multinational corporations were imparting all of their real-world work experiences into their lectures; mind you, they consisted of divisional heads, CTOs, and architects in their respective fields of specialty. What was most extraordinary was the sheer number of modules taught and the variety of perspectives offered through those modules.All of the theories we had learned in class and, most crucially, how to master structured thinking had to be put to the test in our end-to-end, real-time capstone projects, which had to be designed, implemented, deployed, presented, documented, and published. After receiving my degree, I was able to say with a guarantee that it was more than just PAISA WASOOL. Not because I was able to earn a degree which I would have otherwise received from any institution. However, the kind of super churning I went through has given me such a strong sense of fulfilment and confidence.I feel I can challenge anyone to give me any business analytics challenges, and I will not let them down by letting them doubt my abilities and knowledge levels, which I was able to enhance through my degree program at RACE Reva University.
Prakash KonetiPrakash Koneti
15:05 08 Apr 23
I am pursuing Msc in Artificial Intelligence in RACE. I would like to provide honest review on 2 categories..Academics: As working professional I felt bit heavy with Subjects but professors are really coming from realtime background and helps to resolve the doubts.. structured curriculum makes journey smoother.Campus: Definitely you would feel campus like some foreign would love to visit every Saturday without hesitation..
Sam AshishSam Ashish
11:41 24 Jan 23
I highly recommend REVA Academy for Corporate Excellence (RACE) for anyone looking to advance their professional skills. The courses offered are top-notch and cover a wide range of topics, from management and leadership to finance and marketing. The instructors are experts in their respective fields and provide valuable insights and real-world examples. The online platform is easy to use and the materials are well-organized. I particularly appreciated the interactive nature of the classes and the opportunity to network with other professionals. Overall, RACE is an excellent investment in personal and professional growth.
Sandeep BajajSandeep Bajaj
10:12 20 Dec 22
Incredible campus, with spectacular LABS & Infrastructure for students. REVA RACE programs crafted to perfection to upskill your learning pathway. Selective industries experts, faculties makes the journey even more intuitive. Student - Batch 04
I pursued my MBA in Business Analytics from Race and it was a great experience! It paved my career into IT since I came from a hardcore business background. The RACE team helped in finishing the course on time and guided immensely to ensure our projects were meaningful and added value to our careers.
Sathya SubbiahSathya Subbiah
11:34 10 Nov 22
REVA RACE Cybersecurity program offers industry-driven curriculum which is delivered by industry experts. The program includes certifications which are accepted across the globe. The lab and tools facilities available help to have good hands-on. The program definitely helps working professionals to upskill and to move ahead in their career.


RACE, REVA University is an academic partner for AWS, Microsoft, and CloudxLabs and others. The program participants will get unlimited access to our educational partners’ ecosystem, which includes the Cloud labs access, Course Materials, Partners’ LMS, placement services, mentoring sessions, and more.

Microsoft Azure is the leading cloud platform and productivity company for the mobile-first, cloud-first world, and its mission is to empower every person and every organization on the planet to achieve more. Through this partnership, our participants will get access to their 100’s of courses, certification opportunities, and placement services. Cloud labs with credits will be provided to practice the real-time deployment of projects.

AWS Academy partnership provides our participants, course materials to pursue industry-recognized certifications and in-demand analytics / Artificial Intelligence / Machine learning jobs. AWS curriculum helps the learners to stay at the forefront of AWS Cloud innovations. The learners will get access to the Cloud environment to build and deploy Machine Learning / Artificial Intelligence solutions.


Industry mentors are the assets of REVA Academy for Corporate Excellence. The industry experience of our mentors helps the participants to bridge the gap between classroom learning and the industry

Professor and Chief Mentor - AI and CTO, ABIBA Systems
Advisor and Consultant for Generative AI, NuWare
Co-Founder and Chief Architect ,Data Safeguard Inc.
Chief of Research, Exa Protocol | Kaggle Grandmaster and Autism Awareness Champion
Founder, CloudxLab
Consultant - Data Science, Dell Technologies
Founder and CEO, Stealth Startup
CEO and Founder,
Managing Director - Global Hybrid Cloud Leader, Accenture
Manager - Data Science & AI, Publicis Sapient
Co-Founder and CEO, TheMathCompany
Director of Professional Services - APJ, EnterpriseDB
Founder, Analytic Edge Pvt. Ltd.
Innovator, Maestro Technologies, Inc. | Founder and CEO i2i

Continuous Evaluation

This is a globally accredited program to make the participants truly global citizens. At par with international standards and to provide opportunities for global mobility to our participants, we follow an outcome-based education system (OBE). Experiential learning and project-based pedagogy have been employed in the design and delivery of the program.

The objective of module assessment and evaluation is to objectively assess the learners of the program on their ability to apply the concepts, modeling techniques in various domains and verticals for different business scenarios through a continuous evaluation framework throughout the program. Detailed regulations on earning the credits and GPA’s will be shared during the program.


Admission Process

  • Fill the application form
    Register by filling up the
    online application form
  • Get Evaluated
    Go through the documentation process and a screening call with the Director’s office.
  • Join the Program
    If selected, you will receive an ‘offer of admission’ letter for the upcoming cohort. Secure your seat by paying the admission fee.
Upto INR 20,000 Discount

Merit Scholarship

for those who scored


and above in their pre-qualifying exam

Early bird/group/referral
discounts are also available.

Admission Process

Financial assistance and Educational Loans from NBFC’s and Banks are available with interest rate ranging from 9 to 14%. These financial institutions will allow you to repay the educational loan in easy installments and income tax benefits.

Avail hassle-free educational loan to help you to join our Master’s programs to power up your skills to build your dream career.

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