Post Graduate Diploma in Machine Learning and Artificial Intelligence (E-Learning)

Discover the basics of AI and machine learning and learn how to use them effectively to solve complex, real-world problems.


Fully Online Format


13 Months

Recommended 10-15 hrs/week

31 March,2024

Start Date

30 April, 2025

End Date

Programme Overview

Key Highlights

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PG Diploma from upGrad Institute

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360 Degree Career Support

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1:1 Career Coaching

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Live Sessions by Industry Experts

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More than 25 Live Learning Sessions

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200+ Hours of Learning

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Student Support Available All Days

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AI Profile Builder

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Industry Based Projects & Case Studies

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25+ Industry Projects Available

Why pursue a career in ML and AI?
With a constantly growing market, AI and ML is in every Industry, top businesses and across functions.  From supply chain to business development, business analytics, digital marketing, and more. AI and ML today open up more opportunities and career options than ever before. Champion the most in demand skills and be armed with the skills of the future.


Upon successful completion of the Programme, you will receive a Post Graduate Diploma in Machine Learning and Artificial Intelligence from upGrad Institute.
Earn a Post Graduate Diploma in Machine Learning and Artificial Intelligence from upGrad Institute and
Upon successful completion of the Programme, you will receive a Post Graduate Diploma in Machine Learning and Artificial Intelligence from upGrad Institute.<br>Earn a Post Graduate Diploma in Machine Learning and Artificial Intelligence from upGrad Institute and
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  • Be part of the global upGrad community
  • Network with like-minded individuals and learners
  • Access and learn from global subject matter experts
  • Enhance your Machine Learning and Artificial Intelligence skills
  • Real world Machine Learning and Artificial Intelligence Industry Driven Projects & Case Studies
Top Topics You Will Learn
Machine Learning, Deep Learning, Computer Vision, Natural Language Processing, Transformers, Cloud and MLOps. view more
Graduation Requirements

A Post Graduate Diploma in Machine Learning and Artificial Intelligence (E-Learning) will be awarded to students who fulfill:

  • Completion of the course  
Students will be assessed based on Assignments, Projects and Written Examinations.

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Who Is This Programme For?
Engineers, Software and IT Professionals, Data Professionals. view more
Minimum Eligibility
Minimum Age: 21 Years Old
Academic Level: At least Bachelor’s degree in any discipline or; Matured candidates who are at least 30 years old and above with 8 years of work experience and a Diploma and;  Obtained a score of at least 25 marks in the Math section and 20 marks in the Programming section of the admission test.
Language Proficiency: Bachelor's degree where English is the mode of delivery, or IELTS 6.0, or equivalent.* 
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Best-in-class content by leading faculty and industry leaders in the form of videos, case studies, and projects

Programme Developed with Global Experts


Best in class curriculum designed by leading faculty and industry practitioners

  • 1:20

    Teacher-Student Ratio

  • 600+

    Hours of Learning

  • 35+

    Live Learning Sessions

  • 13 Months

    Curriculum Duration

  • Learn how to find and analyse the patterns in the data to draw actionable insights.
  • Learn version control, collaborating, portfolio making using git. Understand the process of creating a repository.Learn the process of creating git hub portfolio using git hub pages with Jekyll.
  • Build a strong statistical foundation and learn how to 'infer' insights from a huge population using a small sample.
  • Understand how to formulate and validate hypotheses for a population to solve real-life business problems.
  • Determine which customers are at the risk of default and what are their characteristics to avoid providing loans to similar people in the future.

  • Venture into the machine learning community by learning how one variable can be predicted using several other variables through a housing dataset where you will predict the prices of houses based on various factors.
  • Build a model to understand the factors car prices vary on and help a Chinese company enter the US car market.
  • Learn your first binary classification technique by determining which customers of a telecom operator are likely to churn versus who are not to help the business retain customers.
  • Understand the basic building blocks of Naive Bayes and learn how to build an SMS Spam Ham Classifier using Naive Bayes technique
  • Learn the pros and cons of simple and complex models and the different methods for quantifying model complexity, along with regularisation and cross validation

  • Understand generalised regression and different feature selection techniques along with the perils off over fitting and how it can be countered using regularisation.
  • Build a model to understand the factors house prices vary on and help an American company enter the Australian housing market.
  • Learn how to find a maximal marginal classifier using SVM, and use them to detect spam emails, recognise alphabets and more!
  • Learn how the human decision-making process can be replicated using a decision tree and other powerful ensemble algorithms.
  • Given a business problem, how do you choose the best algorithm? Learn a few practical tips for doing this here
  • Learn how weak learners can be 'boosted' with the help of each other and become strong learners using different boosting algorithms such as Adaboost, GBM, and XGBoost.
  • Learn how to group elements into different clusters when you don't have any predefined labels to segregate them through K-means clustering, hierarchical clustering, and more.
  • Understand important concepts related to dimensionality reduction, the basic idea and the learning algorithm of PCA, and its practical applications on supervised and unsupervised problems.
  • Solve the most crucial business problem for a leading telecom operator in India and southeast Asia - predicting customer churn.

  • Learn the most sophisticated and cutting-edge technique in machine learning - Artificial Neural Networks or ANNs
  • Learn the basics of CNN and OpenCV and apply it to Computer Vision tasks like detecting anomalies in chestX-Ray scans, vehicle detection to count & categorise them to help the government ascertain the width and strength of the road.
  • Build a neural network from scratch in Tensorflow to identify the type of skin cancer from image
  • Ever wondered what goes behind machine translation, sentiment analysis, speech recognition etc.? Learn how RNN helps in these areas having sequential data like text, speech, videos, etc
  • Make a Smart TV system which can control the TV with user’s hand gestures as the remote control

  • Do you get annoyed by the constant spams in your mailbox? Wouldn't it be nice if we had a program to checkyour spellings?
  • Learn how to analyse the syntax or the grammatical structure of sentences using POS tagging and Dependency parsing.
  • Use the techniques such as POS tagging and Dependency parsing to extract information from unstructured text data
  • Learn the most interesting area in the field of NLP and understand different techniques like word-embeddings, topic modelling to build an application that extracts opinions about socially relevant issues.
  • In this case study you will create a solution that will help in identifying the type of complaint ticket raised by the customers of a multinational bank

  • Understand what is cloud computing, benefits of cloud computing, Different types of cloud providers: Private, public, hybrid. Iaas, Paas, Saas.
  • In this case study you will work on a machine learning task using AWS services
  • Do you think ML ends with just deploying a ML solution? You have to monitor the performance and keep updating the model and its infrastructure from time to time. Learn how to productionize ML model in an end-to-end system in this module.
  • In the assignment you will build and run a complete ML pipeline end-to-end
  • Apply the concepts learned in Neural Networks to advanced computer vision tasks like Object Detection,Semantic Segmentation using YOLO, SSD, UNet, MaskRCNN.
  • It will also introduce you to the evolving world of deep learning for different NLP related applications. and will help you gain a complete understanding of how these complex models work. You will learn how deep learningcan be used for solving different NLP related tasks usingconcepts like attention mechanisms and transformers.
  • In this case study you will learn how to automate a deep learning task by building an end-to-end machine learning pipeline with Amazon SageMaker Pipelines.

  • Introduces students to the world of generative AI and various LLMs that have revolutionised the current industry, and enables learners to dive into that revolution by learning the nitty-gritties of writing a prompt to generate a desired output for complex tasks.
  • Dive deeper into prompt engineering and learn how to structure prompts and outputs, and how you can use advanced prompting techniques such as chain-of-thought prompting, zero- and few-shot prompting, prompt injunctions, prompt parameter tuning. By the end of thismodule, learners will become proficient at definingprompts for most complex tasks.
  • Learn the fundamentals of product development, and deploy your own GPT-enabled web app with the use of Flask.
  • Understand the fundamentals of design, photography and product development to generate images and multi modal outputs for businesses.
  • Write prompts to generate accurate codes for various general and data tasks, perform basic data processing and modelling tasks using ChatGPT and Copilot.
  • Apply your learnings to create various GenAI enabled applications such as Interview Gynie, PixxelCraft and ShrewdNewsAI
  • Understand the concepts of embeddings and take the first step towards building custom LLMs that involve integrating a database with your GenAI models.
  • Embed large documents and datasets with the help of vector stores like Pinecone to enhance ChatGPT's ability to understand context, avoid hallucinations, and perform accurately on data-specific tasks.
  • With the limitations of standalone LLMs, understand how LangChain can be used to overcome those limitations and help integrate GenAI models on specific data pools.
  • Understand how the different components of LangChain such as Models, Prompts, Indexes, Chains, Memory andAgents help building a GenAI model.
  • Understand how to connect components using chain, and how different inbuilt tools in LangChain can be leveraged for your models.
  • Deploy your generative AI models using Azure OpenAI services and understand the considerations that go in when scaling generative AI models.
  • Understand what the future of AI holds (mitigating risks in AI, RLHF as a product, Multimodal Learning), both from the architecture and applications perspective.

  • Choose from a range of real-world industry woven projects on advanced topics like Recommendation Systems, Fraud Detection, GANs among many others.
  • Build a model to using the concepts of natural language processing and recommender systems to recommend news stories to users on a popular news platform.
  • To build a machine learning model capable of detecting fraudulent transactions. Here you have to predict fraudulent credit card transactions with the help of machine learning models.
  • Build a model that can help any visually impaired person in understanding the image present before them. It is a deep learning model which can explain the content of an image in the form of speech.
  • Build a sentiment analysis based product recommendation system to recommend the similar products to the users. Sentiment analysis is used to fine tune the product recommendation system.
  • Predict the sales for a European pharma giant using a host of different types of variables. Apply VAR and VARMAX models to build the appropriate model
  • Build a Model for converting MRI images from one type (T1) into other (T2) and vice versa.
  • Predict the sales for a European pharma giant using ahost of different types of variables. Apply VAR and VARMAX models to build the appropriate model
  • Build a Model for converting MRI images from one type (T1) into other (T2) and vice versa.

Industry Projects

Learn through real-life industry projects.
  • Engage in collaborative projects with student-mentor interaction
  • Benefit by learning in-person with expert mentors
  • Personalised descriptive feedback on your submissions to facilitate improvement

The upGrad Institute Advantage

Strong hand-holding with dedicated support to help you navigate your PGD in Machine Learning and Artificial Intelligence.


Student Support (Non-Academic queries)

  • Student Support Team is available 24*7
  • Email us on studentsupport@upgrad.com OR use the "Talk to Us" option on the learning platform

Doubt Resolution (Academic)

  • Live Discussion forum for peer to peer doubt resolution monitored by technical experts
  • 1-1 Doubt solving sessions with Teaching Experts
  • Informal peer groups on WhatsApp to clear doubts 


Industry Networking

  • Global alumni network based in over 85 countries
  • Virtual networking sessions with classmates and alumni
  • Online discussion forums for peer to peer interaction
  • Learn and network with our industry experts and career coaches
  • Informal peer groups on WhatsApp for learners to interact and network

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  • Career webinars for industry leaders to guide you on your career path and job opportunities available in the field of Machine Learning and Artificial Intelligence.
  • Resume and LinkedIn profile building support, to enhance your career prospects.
  • Global job opportunities.

20 Programming Languages, Tools & Libraries Covered

Career Impact


Career Coaching (1:1)

(1:1) with a dedicated career coach to build your career path.

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Career Webinars

Industry leaders to guide you on job opportunities, career path in the field of Machine Learning and Artificial Intelligence

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Profile Builder

Resume and LinkedIn Profile Building to enhance your career.

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Interview Preparation

Support on polishing your hard skills and soft skills for interview preparation. Access to Just-In-Time Interviews and company specific preparation.

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Admission Process


Course Fee : SGD $ 6,000

Application Fee: SGD $700

*Fees stated are inclusive of GST

Refer someone you know and receive cash reimbursements of up to SGD 650!*
*More details under the referral policy under Support Section

How will you benefit from this programme

  • PGD in Machine Learning and Artificial Intelligence from upGrad Institute
  • Get PGD in Machine Learning and Artificial Intelligence without quitting your job
  • Career Acceleration in your current role
  • Up your Tech-related Skills
  • Cutting-edge curriculum designed by industry experts

Empowering the learners of today to be the leaders of tomorrow!


Frequently Asked Questions

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