PG Diploma in Machine Learning and AI

The Postgraduate Diploma in Machine Learning and Artificial Intelligence (E-Learning) is a comprehensive 9-month online program that equips you with fundamental knowledge in AI and machine learning. Through expert-led instruction and hands-on projects, you'll master essential concepts in supervised and unsupervised learning, artificial intelligence applications, and practical implementation using Python. The program features a balanced mix of theoretical foundations and real-world applications, preparing you to solve complex business problems using cutting-edge AI technologies.

Instructors:

John W. Paisley

Ansaf Salleb-Aouissi

English

Duration:
9 Months

₹ 2,89,148

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Overview

This comprehensive postgraduate diploma program offers advanced training in machine learning and artificial intelligence through a flexible online learning format. The curriculum combines theoretical foundations with practical applications, preparing professionals to implement AI solutions across various industries.

Why Postgraduate Diplomas?

Our program stands out through its industry-relevant curriculum, expert faculty from Columbia University, hands-on projects using real datasets, and flexible online learning format. The comprehensive coverage of both ML and AI concepts ensures graduates can tackle complex real-world challenges.

What does this course have to offer?

Key Highlights

World-class faculty from Columbia University
Flexible online learning format
Hands-on experience with real-world projects
Comprehensive curriculum covering both ML and AI
Industry-relevant case studies and applications
Global networking opportunities
Verified digital diploma upon completion

Who is this programme for?

Working professionals seeking to transition into AI/ML roles
Software developers wanting to specialize in AI
Data analysts looking to upgrade their skills
Technology managers needing AI expertise
Professionals from any field interested in AI applications

Minimum Eligibility

Bachelor's Degree in any discipline
Intermediate knowledge of Python
Basic knowledge of statistics, calculus, and linear algebra
Minimum age of 21 years
English language proficiency

Who is the programme for?

The admission process includes an application review, eligibility test in statistics and mathematics, and verification of Python programming skills. Academic requirements include a bachelor's degree in any discipline and English language proficiency. The program offers a complementary Python course to help meet prerequisites.

Important Dates

Selection process

How to apply?

Curriculum

The curriculum is structured into three main modules: Applied Machine Learning, Applied Artificial Intelligence, and a Capstone Project. Each module builds progressively from foundational concepts to advanced applications, ensuring a thorough understanding of both theoretical principles and practical implementations.

There are 3 semesters in this course

The program begins with Applied Machine Learning, covering supervised and unsupervised learning techniques. The second module focuses on Artificial Intelligence, including intelligent agents, search algorithms, and reinforcement learning. The final module involves a comprehensive capstone project applying learned concepts to real-world problems.

Module 1: Applied Machine Learning

Module 2: Applied Artificial Intelligence

Module 3: Capstone Project

Programme Length

Nine months of intensive online learning

Tuition Fee

The program fee is structured to provide maximum value while remaining accessible. Multiple payment options and early bird discounts are available. The investment reflects the comprehensive nature of the curriculum and the quality of instruction from Columbia University faculty.

Fee Structure

Payment options

Financing options

Financial Aid

Learning Experience

The program utilizes a multi-modal learning approach combining video lectures, live online sessions, interactive discussions, and hands-on projects. The teacher-student ratio of 1:300 ensures personalized attention while maintaining collaborative learning opportunities.

University Experience

Students gain access to Columbia University's academic excellence through expert faculty and cutting-edge curriculum. The program provides opportunities for global networking and includes access to the Emeritus Network benefits after completion.

About the University

Columbia Engineering, established in 1864, is the engineering and applied science school of Columbia University. Originally founded as the School of Mines, it was renamed in 1997 following a $26 million donation from Z.Y. Fu. The school maintains strong research partnerships with organizations like NASA, IBM, MIT, and The Earth Institute. The institution is known for groundbreaking technological achievements including the development of FM radio and the maser. Located in New York City, it offers comprehensive programs across various engineering disciplines and applied sciences, emphasizing innovation, interdisciplinary research, and practical applications.

#18

US news engineering ranking

5011

Total enrollment

4%

Acceptance rate

Affiliation & Recognition

IBM

MIT

Columbia University

The Earth Institute

Career services

Columbia Engineering provides comprehensive career support through its Engineering Career Center. The center organizes regular career fairs, industry networking events, and professional development workshops. Students benefit from personalized career counseling, resume reviews, and interview preparation services. The school's strong ties with industry partners, particularly in New York City's tech sector, create valuable internship and job placement opportunities. The institution's location in New York City offers unique advantages for career development, with direct access to numerous technology companies, startups, and major corporations. The career center also facilitates connections with Columbia's extensive alumni network, providing mentorship opportunities and industry insights.

100

Industry partnerships

85,000

Average starting salary

Top Recruiters

Duration:
9 Months

₹ 2,89,148

Add to compare

Whom you will learn from?

Learn from top industry experts who bring real-world experience and deep knowledge to every lesson. The instructors are dedicated to help you achieve your goals with practical insights and hands-on guidance.

Instructors

John W. Paisley

Associate Professor of Electrical Engineering at Columbia University

John W. Paisley is an Associate Professor of Electrical Engineering at Columbia University and an affiliated member of the Data Sciences Institute. His research focuses on Bayesian models and inference techniques for large-scale text and image processing. He holds a PhD from Duke and has conducted postdoctoral research at Princeton and UC Berkeley.

Ansaf Salleb-Aouissi

faculty at Columbia University

Ansaf Salleb-Aouissi is a faculty member in the Department of Computer Science at Columbia University. She specializes in machine learning and AI, with research in rule learning, action recommendation, and medical informatics. She earned her PhD from the University of Orleans, France, and has worked at Columbia’s Center for Computational Learning Systems.

Testimonials

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Faculties

These are the expert instructors who will be teaching you throughout the course. With a wealth of knowledge and real-world experience, they’re here to guide, inspire, and support you every step of the way. Get to know the people who will help you reach your learning goals and make the most of your journey.

Instructors

John W. Paisley

Associate Professor of Electrical Engineering at Columbia University

Ansaf Salleb-Aouissi

faculty at Columbia University

Frequently asked questions

Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.

What are the prerequisites for the program?

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