Key Highlights of the Artificial Intelligence and Machine Learning course

Designed for Working Professionals
Pursue MS in AIML for under USD 7500
12 Hands-on Projects and 30+ Case Studies
1 Capstone Project at the end of each Year
Get Alumni Status from Walsh College
No GRE/GMAT or TOEFL Requirement
Includes modules on ChatGPT and GenAI

Skills you will learn

Machine Learning
Data Science
AI Engineering
Python
SQL
Data Analysis
Applied Statistics
Generative AI
Prompt Engineering
Deep Learning
Neural Networks

Program Curriculum

Post Graduate Program in AI and ML

Foundations

PYTHON FOR AI AND MACHINE LEARNING
This course focuses on Python programming used for Artificial Intelligence and Machine Learning. Learners will work on a high-level idea of Object-Oriented Programming and later
learn the essential vocabulary (keywords), grammar (syntax) and sentence formation (usable code) of this language. This module will drive learners from introduction to AI and ML to the core concepts using one of the most popular and advanced programming languages - Python.

APPLIED STATISTICS
Learn the terms and concepts vital to Exploratory Data Analysis and Machine Learning in general. From the very basics of taking a simple average to the advanced process of finding statistical evidence to confirm or deny conjectures and speculations, learners will focus on a specific set of tools required to analyze and draw actionable insights from data.

INTRODUCTION TO DATA SCIENCE AND AI (SELF-PACED)
Gain an understanding of the evolution of AI and Data Science over time, their application in industries, the mathematics and statistics behind them, and an overview of the life cycle of building data driven solution:

The fascinating history of Data Science and AI
Transforming Industries through Data Science and AI
The Math and Stats underlying the technology
Navigating the Data Science and AI Lifecycle

Machine Learning

SUPERVISED LEARNING
Learn about Supervised ML algorithms, working of the algorithms and their scope of application - Regression and Classification.

UNSUPERVISED LEARNING
Learn about Unsupervised Learning algorithms, working of these algorithms and their scope of application - Clustering and Dimensionality Reduction.

ENSEMBLE TECHNIQUES
In this Machine Learning module, work on supervised standalone models’ shortcomings and learn a few techniques, such as Ensemble techniques to overcome these shortcomings.

FEATURIZATION, MODEL SELECTION AND TUNING
Learn various concepts that will be useful in creating functional machine learning models like model selection and tuning, model performance measures, ways of regularization, etc.

INTRODUCTION TO SQL
Know about SQL programming, such as DBMS, Normalization, Joins, etc.

Artificial Intelligence

INTRODUCTION TO GENERATIVE AI AND PROMPT ENGINEERING
This module offers a comprehensive exploration of two critical aspects of Artificial Intelligence. Through live sessions, learners will delve into the fundamental concepts and techniques of generative AI, a field known for its innovation and creativity. Learners will also master the practical applications of prompt engineering, including designing effective prompts, optimizing results, and exploring various prompt engineering techniques.

INTRODUCTION TO NEURAL NETWORKS AND DEEP LEARNING
In this Artificial Intelligence module, learners understand the motive behind using the terms Neural Network and look at the individual constituents of a Neural Network, installation of and building familiarity with TensorFlow library, appreciate the simplicity of Keras and build a deep neural network model for a classification problem using Keras. They also learn how to tune a Deep Neural Network.

COMPUTER VISION
In this Computer Vision module, learn how to process and work with images for image classification using Neural Networks. Going beyond plain Neural Networks, learners will also focus on a more advanced architecture - Convolutional Neural Networks.

NATURAL LANGUAGE PROCESSING
Learn how to work with Natural Language Processing with Python using traditional Machine Learning methods. Then, deep dive into the realm of Sequential Models and state of the art language models.

SELF-PACED MODULE: DEMYSTIFYING CHATGPT AND APPLICATIONS
Gain an understanding of what ChatGPT is and how it works, as well as delve into the implications of ChatGPT for work, business, and education. Additionally, learn about prompt engineering and how it can be used to fine-tune outputs for specific use cases.

SELF-PACED MODULE: CHATGPT - THE DEVELOPMENT STACK
Dive into the development stack of ChatGPT by learning the mathematical fundamentals that underlie generative AI. Further, learn about transformer models and how they are used in generative AI for natural language.

Capstone Project

Get your hands dirty with a real-time project under industry experts’ guidance. This covers everything from an introduction to Python and Artificial Intelligence to Machine Learning. Successful completion of the project will earn you a Post Graduate Certificate.

MS in AI and ML

Term 1

IT 721 : APPLIED RESEARCH TOPICS IN DEEP LEARNING THEORY & PRACTICAL APPLICATIONS:
In this course, you will master CNNs, RNNs, LSTMs, autoencoders, and state-of the-art generative models like GPT, PaLM, CLIP, and DALL·E and gain the industry-critical skills of transfer learning, prompt engineering, and RAG & LoRA fine-tuning to create domain-specific AI systems ready for real-world impact.Database storage technologies have transformed into complex systems that support knowledge management and decision support systems. This course takes a look at the foundations of database storage technologies. Students will learn about database storage architecture, types of database storage systems (legacy, current and emerging), physical data storage, transaction management, database storage APIs, data warehousing, governance and big data systems. The student will tie this all together to see how database storage technologies apply to data analytics.

Introduction to Deep Learning
Neural Networks & Backpropagation
CNN, RNN, LSTM
Autoencoders & Generative Models
Transfer Learning
Prompt engineering basics
Foundation Models GPT, PaLM, CLIP, DALL·E
RAG, LoRA

IT 547 : DATA STORAGE TECHNOLOGIES:

Database storage technologies have transformed into complex systems that support knowledge management and decision support systems. This course takes a look at the foundations of database storage technologies. Students will learn about database storage architecture, types of database storage systems (legacy, current and emerging), physical data storage, transaction management, database storage APIs, data warehousing, governance and big data systems. The student will tie this all together to see how database storage technologies apply to data analytics. Upon successful completion of this course, you will be able to:

Evaluate different database storage technologies.
Compare systems used in data analytics.
Investigate legacy, current, and emerging systems.
Assess database storage solutions through hands-on labs.

Term 2

BTC 771 : AI STRATEGY FOR LEADERS:

The course integrates real-world case studies from industry leaders such as Tesla, Amazon, JPMorgan Chase, and Microsoft, providing students with insights into AI successes and challenges. Through case study analyses, discussions, and practical assignments, students will develop leadership strategies for AI integration, ensuring responsible and effective AI adoption in their organizations.

AI Fundamentals and Business Applications
AI Vision and Strategy Development
Ethical AI Leadership
Building AI-Ready Teams
AI Tools and Technologies
Data Governance and Compliance
Measuring AI Impact and Risks
The Future of AI Leadership

QM 625 : Mathematics of Artificial Intelligence & Machine Learning

This course introduces and explains the fundamental mathematical concepts that form the backbone of artificial intelligence and deep learning. It emphasizes a strong understanding of linear algebra and analytic geometry, which are essential for building and optimizing AI models. Learners will explore how these mathematical principles directly apply to modern algorithms and neural networks. By the end of the course, participants will gain the analytical skills needed to interpret and implement AI techniques effectively.

Course Learning Outcomes:

Upon successful completion of this course, students will be able to:

Analyze the role of scalars, vector spaces, tensors, matrices, derivatives, and gradient descent in AI and ML.
Apply fundamental linear algebra and its mathematics to solve problems in AI and ML.
Evaluate and select the most effective optimization methods and their mathematics for specific AI and ML problems.
Differentiate between the roles of probability in predicting future events and statistics in analyzing past events for their applications in AI and ML.

Term 3

QM 625 : CAPSTONE PROJECT:

The Capstone Project provides the opportunity for integrating program learning within a project framework. Each student identifies or defines a professionally relevant need to be addressed that represents an opportunity to assimilate, integrate or extend learning derived through the program. The student will work with the Capstone Project Mentor to develop a proposal. After review and approval by the Capstone Project Mentor, the student will be authorized to complete the project.The student will present the completed project at the end of the semester.Upon successful completion of this course, you will be able to:

Demonstrate the knowledge gained from the previous courses in the program.
Write a formal research paper or conduct a detailed project.
Apply the objectives of research to a practical information technology problem.
Create a project plan to successfully present a solution/goal to the stated problem.
Use research tools for an applied research paper or project.
Evaluate the validity and reliability of statistics and other forms of research.

Learning Path

Year 1

Learners will join the Post Graduate Program in AI and Machine Learning by The University of Texas at Austin and Great Lakes Executive Learning and receive PG certificates upon program completion.

Year 2

Post completion of the PG Program in AI and Machine Learning, candidates will continue their learning journey with the MS in Artificial Intelligence and Machine Learning offered by Walsh College.

On-Completion

Successful learners will receive the MS in Artificial Intelligence and Machine Learning from Walsh College.

Earn a Degree and PG Certificate from the world's leading institutions

* Image for illustration only. Certificate subject to change.

WES Recognised
The Higher Learning Commission

Recognized by the U.S. Department of Education

Industry relevant syllabus

Languages and Tools covered

Python
Keras
Numpy
TensorFlow
Matplotlib
Scikit Learn
Seaborn
Statsmodels

Meet the Faculty

Meet the experienced and world-class faculty who will teach you the core concepts of Artificial Intelligence and Machine learning

Javad Katibai

Chassis System Architect - General Motors
Dr. Dave Schippers

VP and Academic Dean
James Gerrity

PhD, Adjunct Associate Professor
Thomas Petz

CIO/COO, Assistant Professor of IT
Christopher Heiden

Program Lead at IT, Associate Professor of Business Information Technology
Dr. Abhinanda Sarkar

Senior Faculty & Director Academics, Great Learning

Dr. Abhinanda Sarkar has B.Stat. and M.Stat. degrees from the Indian Statistical Institute (ISI) and a Ph.D. in Statistics from Stanford University. He was a lecturer at Massachusetts Institute of Technology (MIT) and a research staff member at IBM. Post this he spent a decade at General Electric (GE). He has provided committee service for the University Grants Commission (UGC) of the Government of India, for infoDev – a World Bank program, and for the National Association of Software and Services Companies (NASSCOM). He is a recipient of the ISI Alumni Association Medal, an IBM Invention Achievement Award, and the Radhakrishan Mentor Award from GE India. He is a seasoned academician and has taught at Stanford, ISI Delhi, the Indian Institute of Management (IIM-Bangalore), and the Indian Institute of Science. Currently, he is a Full-Time Faculty at Great Lakes. He is Associate Dean at the MYRA School of Business where he teaches courses such as business analytics, data mining, marketing research, and risk management. He is also co-founder of OmiX Labs – a startup company dedicated to low-cost medical diagnostics and nucleic acid testing.

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Dr. P. K. Viswanathan

Professor, Analytics & Operations
Mr. Gurumoorthy Pattabiraman

Faculty, Data Science & ML, Great Learning

Gurumoorthy is a Techno-Functional Professional with over 10 years of experience in the IT & Analytics domains. He is an undergrad in Mathematics & postgrad in Actuarial Economics. He has headed the Global Analytics Team in one of the World's largest Shipping Companies and currently is the "Head of Industry Solutions" in the Analytics & Mobility spaces at a niche AR/VR/MR Start-up Company in Chennai. He has handled over 400 hours of Analytics training classes/workshops for Corporate and Individuals early in his career. He started his career as an Entrepreneur, handling clients on multiple Web Analytics & SEO/SEM Consulting Projects.

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Prof. Dipayan Sarkar

Consultant, Author, Visiting Faculty

Prof. Dipayan Sarkar is a passionate data scientist and AI Researcher professional who loves to ‘think big’, supporting iconic international brands and consulting firms brands to reach their full potential through the development and execution of compelling project strategies, driving projects and generating significant returns.

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Note: The above faculty list is indicative

Get Industry ready with Dedicated Career Support

GL-Excelerate

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Job board with 100+ postings

Access our Job Boards where our team posts job opportunities from top organizations
1 on 1 Mentoring from industry experts

Get 1 : 1 career mentoring with LIVE online sessions with industry professionals
Career Services

Gain industry insights and set your career goals with mentorship
Build your career profile

We provide students with sample SOP formats to guide them in crafting a compelling SOP.
Mock Interviews & Alumni Connect

Participate in mock interviews & get guidance from our alumni currently in roles you aspire for

Application process

Our admissions close once the requisite number of participants enroll for the upcoming batch. Apply early to secure your seats.

1. Apply Online

Fill out a fast and easy online application form. No additional tests or prerequisites are needed.
2. Pre-Screening

Our team will make contact with you by phone to confirm your eligibility for the program.
3. Application Assessment

If selected, you will receive an offer for the upcoming cohort. Secure your seat by paying the fee.
4. Join the program

If selected, you will receive an acceptance letter with instructions on how to pay and join the program.

Limited seats available

Apply today and become a Artificial Intelligence and Machine learning Expert

Eligibility

Applicants must hold a 3 or 4-year bachelor’s degree or equivalent in any discipline with a minimum of 60% marks from a UGC-recognized university or institution. The medium of instruction must be in English.
No GRE/GMAT or any English proficiency test scores are required.

Note: Candidates should score a minimum of 2.75 CGPA in the 1st year to be eligible for 2nd year on campus at Walsh College.

Batch Start Date

Online · To be announced

Admissions Open

Apply Now

Frequently asked questions

Program Details

What are the key highlights of the MS in Artificial Intelligence and Machine Learning program?

The program offers the following key highlights:

A fully online, two-year master’s degree from Walsh College
12 hands-on projects and over 30 case studies
Capstone projects at the end of Year 1 and Year 2
An industry-relevant curriculum with dedicated modules on ChatGPT and Generative AI
Instruction from experienced faculty and industry practitioners
Alumni status from Walsh College upon successful completion

What is the duration of the MS in Artificial Intelligence and Machine Learning program?

The MS in Artificial Intelligence and Machine Learning is a two-year, fully online program offered by Walsh College.

Is the program offered online or on campus?

The program is delivered entirely online, allowing learners to study from anywhere.

Who offers this program?

The MS in Artificial Intelligence and Machine Learning program is offered by Walsh College, a private, not-for-profit institution based in the United States.

What will I learn in this program?

On successfully completing this MS in AIML program, you will be able to:

Review and report on AI and Machine Learning processing to understand data within a larger context.
Become an ideal candidate for high-demand fields such as AI research, Data Science, and AI engineering.
Apply new-age AI techniques to solve real-world business problems.
Contribute to cutting-edge AI research and advancements in technology and science.
Develop a mindset for continuous learning in the rapidly evolving fields of AI and ML.

What does the curriculum of the MS in AI and ML focus on?

The curriculum focuses on advanced applications of Artificial Intelligence and Machine Learning. It is designed to build both theoretical understanding and practical skills through hands-on projects, case studies, and real-world applications, preparing learners to apply AI and ML techniques in business and technology contexts. It includes modules on Generative AI, ChatGPT, Deep Learning, Computer Vision, Natural Language Processing, and Data Science.

Are there hands-on projects included in the program?

Yes. The program includes 12 hands-on projects, over 30 case studies, and capstone projects at the end of Year 1 and Year 2.

Will I earn any additional credentials during the program?

Yes. Upon successful completion of the Year 1 requirements, you will earn a Post Graduate Certificate in AI and Machine Learning from The University of Texas at Austin and Great Lakes Executive Learning, in addition to the MS degree from Walsh College awarded after Year 2.

What tools and technologies are covered in the program?

The program covers industry-relevant languages and tools, including Python, SQL, TensorFlow, Keras, and technologies used in Artificial Intelligence and Machine Learning applications.

Admissions and Eligibility

What is the eligibility criteria for this program?

Applicants must hold a 3 or 4-year bachelor’s degree or equivalent in any discipline from a recognized university or institution. The medium of instruction must be in English.
No GRE/GMAT or any English proficiency test scores are required.

Note: Candidates should score a minimum of 2.75 CGPA in the 1st year to be eligible for the 2nd year of the program.

Are GRE, GMAT, or English proficiency tests required?

No. GRE, GMAT, TOEFL, or other English proficiency test scores are not required for admission.

Is there a minimum academic requirement to progress in the MS in AIML?

Yes. Candidates must score a minimum CGPA of 2.75 in the first year to be eligible to continue into the second year of the program.

What is the admission process?

Great Learning provides end-to-end support for the Walsh College application process.

Step 1: APPLY ONLINE

Fill out a fast and easy online application form.
No additional tests or prerequisites are needed.

Step 2: PRE-SCREENING

Our team will reach out to you to confirm your eligibility for the program.

Step 3: APPLICATION ASSESSMENT

The Admissions Team will assess your application and provide a timely response.

Step 4: JOIN THE PROGRAM

If selected, you will receive an acceptance letter with instructions on how to pay and join the program.

Note: Candidates should score a minimum of 2.75 CGPA in the 1st year to be eligible for the 2nd year of the program.

*Admission to the program is subject to Walsh College acceptance.

Does Great Learning support the admission process?

Yes. Great Learning provides end-to-end support throughout the Walsh College application process.

Fee and Payment

What is the total program fee for an MS in AI and ML?

The total program fee is INR 5,50,000 + GST.

Is admission guaranteed after fee payment?

No. Admission to the program is subject to acceptance by Walsh College.

General Queries

Is Walsh College accredited?

Yes. Walsh College is accredited by The Higher Learning Commission (HLC), a regional accreditation agency recognized by the U.S. Department of Education.

Is the degree recognized internationally?

Walsh College is recognized by World Education Services (WES), which helps learners validate their academic credentials for use in the U.S. and Canada.

Will I receive alumni status after completing the MS in AIML?

Yes. Graduates receive alumni status from Walsh College upon successful completion of the program.

Does the MS in AIML program include career support?

Yes. Learners receive career support through resume building, interview preparation, career guidance, and an e-portfolio to showcase projects and skills.