INR 5.2 Lakhs
For M.Tech.: B.Tech/BE in CSE (Related Programs) /ECE/EEE/ISE/IT/TE
For M.Sc.: BCA/B.Sc. in IT/CS/Electronics or B.Com./BBA with Computer Applications, they should have studied Mathematics or Statistics at +2 level (Mandatory) or Any B.Tech/BE degree including M.Tech, Civil, or MCA or M.Sc. in IT/IS/CS. Minimum of 50% marks (45% in case of SC/ST candidates) in aggregate of any recognised university/institution or any other qualification recognised as equivalent thereto. Relevant work experience of 2 years above in related field ininformation security or related fields.
Exclusive Cyber Range as Simulator
Cyber Range is an infrastructure deployed to reproduce a real-life security infrastructure just like a test lab to train your team(s) to defend against cyberattack scenarios. The participants will get access to this virtual environment on cyber warfare scenarios throughout the program. For beginners, a Cyber Range is composed of 4 teams: Red, Green, Blue, and White in which each participant plays an important role to create a safe and secure environment for enterprises. This exposure to real-time emulator will provide our participants with a comprehensive, detailed and practical learning space to build their cybersecurity skill sets.
The Red Team simulates malicious users launching cyber attacks to the user’s computer with the help of different vectors and install viruses, trojans, worms, spywares, adwares and malwares.
The Green Team simulates legitimate users over wire or wireless connections with their desktops, laptops, tablets, smartphones to the application infrastructure hosted on the network infrastructure managed by Blue Team.
The Blue Team simulates the users managing the availability, the scalability, the security and the stability of network infrastructure and application infrastructure.
The White Team creates the cyber attack scenarios and then monitor the success or failure of Blue Team to defend against cyber attacks launched by Red Team, keeping availability, scalability, security and performance of network infrastructure and application infrastructure for Green Team.
Build a lucrative career path in Artificial Intelligence with the M.Tech./M.Sc. 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.
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.
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.
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.
RACE has also partnered with leading industry giants to ensure the participants achieve their career-oriented goals.
Maximum Salary Hike
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.
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.
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.
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.
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.
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
AWS Academy Machine Learning Foundations introduces students to the concepts and terminology of Artificial Intelligence and Machine Learning. By the end of this course, students will be able to select and apply machine learning services to resolve business problems. They will also label, build, train, and deploy a custom machine learning model through a guided, hands-on approach.
Tools: Amazon SageMaker
This module deals with designing and implementing a data science solution on Microsoft Azure. The participants will learn to create and manage Azure and Databricks workspace, run and monitor models, automated MLs and tune hyperparameters, 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
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.
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
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.
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 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 Vision Services, Video Indexer, Language Understanding Service (LUIS), QnA Maker, etc.
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
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.
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.
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.
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.
The participants will get access to six-plus high-demand courses on an online cloud platform for making learning fun and sustainable. The learning platform is gamified which features an array of one-of-its-kind offerings including -Online Video Courses. 24-hour Lab access (with Jupyter environment), Auto- assessment tests, and BootML – The UI-based Machine Learning model code generator.
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
Prahlad is a Strategist, Industry Leader, Change Expert and a Leadership Coach. He had led several engagements and business units globally by guiding companies in their business, operations, IT and Analytics strategy, and execution. (more…)
Gopal is a leading subject-matter-expert in Cloud, AI, and Automation technologies. He has a proven track record of driving digital transformation at scale for 1K enterprises across multiple industries. (more…)
Sayandeb has worked both as part of the large enterprises by setting up the analytics capabilities as well as a service provider for various enterprises. Sayandeb has also played several intrapreneurial roles like designing training and pedagogy (more…)
Dr. Santosh Nair has extensive experience in statistical modelling and advanced analytics consulting. He has extensive experience in statistical modelling and advanced analytics consulting. His areas of specialization include Marketing and (more…)
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.
A set of researchers is building a Computer-Aided Pronunciation and Reading System (CAPRS). This is an Artificial Intelligence (AI) and Natural Language Processing (NLP) system for one-to-one tutoring with a mobile app/humanoid simulator for primary students to learn different skills in their vernacular languages.
The researchers are building a QnA system with deep learning trained on the Kannada language dataset to evaluate the emotions and recommended answers/actions. This model is used to make a recommendation system for citizen helplines, understand citizens’ voices, and suggest possible measures to decision-makers.
Customer Intelligence based on the Customer Life Cycle Analytics (CLCATM) solution from RACE labs enables anyone to use the packaged AI/DS to understand and serve their customers better.
This solution provides data models and domain models for supply chain analytics. With multiple analytical technologies like the Theory of Constraints (ToC) and Machine learning, the SCAn engine brings the power to provide the controls required to build efficient data-driven supply chain systems. An end-to-end discovery from typical supply chain data, predictive models for inventory planning, demand forecasting, and stock events like stock out are part of this solution.
Financial assistance and Educational Loans from NBFC’s and Banks are available with interest rate ranging from 7.9 to 11%. 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.
Success is in the DNA of RACE. Decipher the successful journey of RACE through our mentors and participants.
“ I’m very grateful and proud to be part of the MBA in Business Analytics program at REVA Academy for Corporate Excellence (RACE), 2019-2021 Batch. The credit goes to RACE mentors and my batch mates. Still, a long way to go to learn and improve my skills.”
“ Being a program/project manager for the past 7 years and with more than 9 years of experience in technologies like Java, .net, DevOps, I got associated with REVA for MBA (Artificial intelligence). I have learnt from classroom sessions with many industry leaders and got exposure to real-time business understanding in AI. The hands-on sessions at RACE helped me a lot in exploring new opportunities in Data Science and the Artificial intelligence world.”
“ I have been associated with REVA University for Corporate Excellence for last 4+ years, working closely with the PGDM/MBA in Business Analytics Batches in delivery, helping with use cases, and some of the data processing areas. Even though the participants joining RACE’s programs are well-experienced, they would like to expand or switch their career for better opportunities. To advance in their career, MBA/PGDM in Business Analytics program of RACE is a great choice.”
“The program added value to my experience in Data Science and Business Analytics domain as the program allowed me to solve real-life problems using machine learning models and data science techniques."
The artificial intelligence domain shows exponential growth in recent years. AI is the subset of Data Science, which helps to simulate machine intelligence. Learning an emerging technology like AI is a great choice as businesses/organizations are becoming dependent on various AI applications. Businesses/organizations rely on AI as it helps to improve products/services, analyze business models, and enhance decision-making processes in businesses. Hence, enrolling to PGD/M. Tech in Artificial Intelligence program at RACE will take your career to the next level.
The demand for artificial intelligence professionals is ever-growing because all of us are living in a technology-driven world. We are creating algorithms that can automate business services and business intelligence. The development of self-driven cars and service robots is creating challenges in the business world. Hence, there is a huge requirement for talented individuals who can change the world with AI applications. AI applications are not limited to the automotive/service industry, but also applicable to every other industry.
According to the academic calendar, admissions to MTech/MSc in Artificial Intelligence will be in two batches, Batch 1 starts in the month of September, and Batch 2 starts in the month of March. However, you can apply for the program or reserve your seats at any time. Admissions will happen throughout the year, but you have to pre-confirm the batch you would like to join.
Click on the ‘Apply Now’ button on our website, https://race.reva.edu.in. You’ll be directed to another page where you can choose your preferred program, which will take you to the next page that consists of all the program details. Use the pop-up form to fill in your details and register.
Once you’ve registered with us, you will get a confirmation mail regarding your registration. Soon after the submission of the registration form, one of our expert executives will contact you and take you through the application process.
Working professionals with a minimum of 50% (45% in the case of SC/ST candidates) in their undergraduate degree of any discipline and 2 years of work experience in the industry are eligible for admission.
Both PG Diploma and M. Tech/M.Sc in Artificial Intelligence is offered in the format of traditional classroom delivery (on-campus), which is on Saturdays. However, short-term programs/certification courses are available in both online and blended learning modes depending on the requirements of the certification courses.
Yes, we provide placement assistance that includes valuable career guidance, tips for creating impressive resumes, and practice interviews. Every participant will receive strong support from industry mentors who will guide you toward various job opportunities in the industry. Placements also occur through recommendations from peers, alumni, and mentors. Above all, we are partnered with leading MNCs that offer placement opportunities to our participants.