Executive PG Program in Machine Learning & Artificial Intelligence
In association with
With Industry Experts From
Program Overview
Key Highlights
Eligibility:
- Bachelor’s Degree with 50% or equivalent passing marks.
- Minimum 1 year of work experience or a degree in Mathematics or Statistics.
Syllabus
Experience 450+ hours of best-in-class content developed by leading faculty & industry leaders in the form of videos, case studies & projects
20 Programming Tools, Languages & Libraries Covered
- Gain IIITB Alumni status & connect with a global network of accomplished IIITB alumni
- Build a strong network for life with opportunities to connect to Machine Learning Industry experts & your experienced fellow learners
Instructors
Learn from India's leading ML & AI faculty and industry leaders
Hindol Basu
Chandrashekar Ramanathan
S. Anand
Tricha Anjali
Ujjyaini Mitra
Prof. Debabrata Das
Anshuman Gupta
Prof. G. Srinivasaraghavan
Ankit Jain
Dinesh Babu Jayagopi
Kalpana Subbaramappa
Srinath Srinivasa
Mirza Rahim Baig
V. Sridhar
Syllabus
Experience 600+ hours of best-in-class content developed by leading faculty & industry leaders in the form of videos, case studies & projects
International Preparatory Course
- Excel MasterClass
- Overview of DS/ML/AI
- Data Visualisation and StoryTelling
- Data Science Problem Solving
- Introduction to Python
- Python for Data Science
- Data Visualisation in Python
- Analytics Problem Solving (Optional)
- Data Analysis Using SQL (Optional)
- Advanced SQL (Optional)
- Programming using Python - I(Optional)
- Programming using Python - II (Optional)
- Data Analysis in Excel (Optional)
- Math for Machine Learning (Optional)
Statistics and Exploratory Data Analytics
- Exploratory Data Analysis
- Cloud Essentials: Intro to Git & Cloud
- Cloud Essentials: Intro AWS
- Investment Assignment
- Inferential Statistics
- Hypothesis Testing
- Lending Club Case Study
Machine Learning - I
- Linear Regression
- Linear Regression Assignment
- Logistic Regression
- Naive Bayes
- Model Selection
Machine Learning - II
- Advanced Regression
- Advanced Regression Assignment
- Support Vector Machine (Optional)
- Tree Models
- Model Selection - Practical Considerations
- Boosting
- Unsupervised learning: Clustering
- Unsupervised Learning: Principal Component Analysis
- Telecom Churn Case Study
Deep Learning
- Introduction to Neural Networks
- Convolutional Neural Networks - Industry Applications
- Convolutional Neural Networks - Assignment
- Recurrent Neural Networks
- Neural Network Project - Gesture Recognition
Natural Language Processing
- Lexical Processing
- Syntactical Processing
- Syntactic Processing - Assignment
- Semantic Processing
- Case Study: Classifying Customer Complaint Tickets
ELective 1: DL with MLops
- Cloud Essentials: Intro to AWS
- Working with AWS: case study
- MLOps: Introduction
- MLOps: Data Lifecycle
- MLOps: Model Lifecycle
- MLops Assignment
- Advanced CV
- Advanced CV
- MLOps + Deployment: DL (Theory)
- MLOps + Deployment: DL (assignment)
Elective 2: NLP with Mlops
- Cloud Essentials: Intro to AWS
- Working with AWS: case study
- MLOps: Introduction
- MLOps: Data Lifecycle
- MLOps: Model Lifecycle
- MLops Assignment
- Advanced NLP
- Advanced NLP
- MLOps + Deployment: NLP (Theory)
- MLOps + Deployment: NLP (assignment)
Elective 3: AI strategy
- Cloud Essentials: Intro to AWS
- Working with AWS: case study
- MLOps: Introduction
- MLOps: Data Lifecycle
- MLOps: Model Lifecycle
- MLops Assignment
- AI Strategy Framework, Structured Problem Solving/ Data Storytelling
- Mapping ML with Data architecture strategy
- Executing AI Strategy
- AI strategy: Assignment
- Capstone
Reinforcement Learning (Optional)
- Classical Reinforcement Learning
- Assignment -Classical Reinforcement Learning
- Deep Reinforcement Learning
- Reinforcement Learning Project
Industry Projects
- Collaborative projects with peers
- In-person learning with expert mentors
- Personalized feedback to facilitate improvement
Telecom Churn Analysis
Solve the most crucial business problem for a leading telecom operator in India and southeast Asia - predicting customer churn.
Train an agent to play Tic Tac Toe
Learners will apply Q-Learning to train an RL agent to play the game of numerical Tic Tac Toe.
Classification of customer complaints
Create a solution that will help in identifying the type of complaint ticket raised by the customers of a multinational bank
Credit Card Fraud Detection
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.
Melanoma Detection Assignment
Build a neural network from scratch in Tensorflow to identify the type of skin cancer from image.
Gesture Recognition
Make a Smart TV system which can control the TV with user’s hand gestures as the remote control
News Recommender System
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.
Maximizing profit of cab driver using RL
Learners will use the Markov Decision Process & Q-Learning to build an RL agent that learns to choose the best request so as to maximize the total profit earned by the agent that day.
Custom Entity detection in Healthcare data
You will build a custom NER to get the list of diseases and their treatment from a medical healthcare dataset.
Eye for the Blind
Build a model that can help any visually impaired person in understanding image present before them. It is a deep learning model which can explain the content of an image in the form of speech.
Sentiment analysis based Product Recommender system
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.
Sales Forecasting
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
Style Transfer using GAN's
Build a Model for converting MRI images from one type (T1) into other (T2) and vice versa. CycleGAN model is used for producing T2 type MRI images given T1 type input MRI images
Machine Translation System
You will build an attention-based neural machine translation model translating from one language to another
Face Mask Detection
Create a custom object detector using the YOLO algorithm to detect the presence of face masks in the images of different people.
The upGrad Advantage
Learning Support
- - Receive unparalleled guidance from industry mentors, teaching assistants and graders
- Fortnightly personalised group (1:8) mentorship sessions with global industry experts for pro-active mentoring
- Calls with industry-experienced experts for personalised feedback & guidance spread over 3 month
- Student Support available all day for your convenience (24*7)
- For urgent queries, use the Call Back option on the platform
Doubt Resolution
- Timely doubt resolution by Industry experts and peers
- 100% Expert-verified responses to ensure quality learning
- Personalized expert feedback on assignments and projects
- Regular live sessions by experts to clarify concept related doubts
Networking
- Live sessions by experts on various industry topics
- One-on-one discussion and feedback sessions with industry mentors
- Worldwide peer to peer networking opportunities with an alumni pool of 10000+
Our Learners Work At
Student Reviews
Anurag Narula
Amarpal Singh
AKNR Chandra Shekhar
Saurav Kant Kumar
Admission Process
Step 1: Take the online eligibility test
Complete your application and take a quick 40-minute online eligibility test on the website with 18 questions to start the admission process. The test is designed to assess your quantitative & logical aptitude ensuring your ready for the program.
Step 2: Get shortlisted & receive your offer letter
Our Admissions Committee will review your test score & profile. Upon qualifying, an offer letter will be sent to you confirming your admission in the Executive PG Program in Machine Learning & Artificial Intelligence.
Step 3: Confirm your seat & begin with your prep - course
Reserve your seat by paying the enrolment amount to enrol in the program. Begin with your preparatory course & start your start your career in Machine Learning.
Program Fees
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Refer someone you know and receive cash reimbursements of up to $500!*
*More details under the referral policy under Support Section
Empowering learners of tomorrow
Over 2,300 students have completed this course and started working at their dream job, whats stopping you?
Frequently Asked Questions
Program Details
How do I know if this program is for me?
Data Scientist or Senior Data Analyst: If you are comfortable with data wrangling, have implemented statistical or machine learning models in the past, and have spent at least 2 years as a working professional. You should also have some experience with R/Python/Scala.
Statistician: If you received formal education in statistics or mathematics and have at least 2 years of working experience.
Data Engineer/Big Data Engineer: If you have at least 2 years of experience in creating data pipelines/handling data warehouses and you have created ETL procedures. In addition, you should be familiar with various frameworks and tools like Hadoop and Spark.
Software Developer: If you have worked on creating and deploying software/apps for at least 4 years, you are comfortable with object-oriented programming and know C/C++/Java/Python or a similar language.
How will this program benefit me?
Data Scientist or Senior Data Analyst: The program will familiarise you with the advancements in ML and AI. It will also help you understand the mathematics behind algorithms and how you can modify them to suit your needs so that you can transition to a Senior Data Science or Machine Learning role.
Statistician/Mathematician: Apart from familiarising you with the advancements in ML and AI, the program will help you understand how to define a structured approach to solve a business problem, and equip you with the right tools so that you can transition to a Machine Learning or Data Science role.
Data Engineer/Big Data Engineer: The program will set up a solid foundation of Statistics, Machine Learning, and AI along with problem-solving skills so that you can solve enterprise-level problems. It will build upon your existing knowledge of various tools to make you a Full-Stack Machine Learning or Data Science professional.
Software Developer: The program will help you create a strong foundation of Statistics, Machine Learning, and Business Understanding. It will leverage your existing knowledge of programming and expand the technologies you are familiar with so that you can become a well-rounded Machine Learning professional.
What is this program intended to do?
What can I expect out of this program?
This program is designed for working professionals looking to pick up skills in advanced concepts like Reinforcement Learning, Graphical Models, NLP, Deep Learning along with a solid foundation of Statistics. This program demands consistent work and time commitment over the entire duration of 12 months.
What should I NOT expect from this program?
This program is NOT intended to serve as an entry point to the field of Data Science. It is aimed at developing professionals who can be absorbed into Senior Data Scientist and Machine Learning/AI roles. Our Executive PG Program in Machine Learning & Artificial Intelligence is aimed at facilitating the transition of professionals to the Data Science field.
Is there any certification at the end of the program?
Post completion of the program, a Executive PG Program in Machine Learning & Artificial Intelligence will be granted from IIIT Bangalore.
Support
What type of learning should I expect?
Refund Policy
Is there any deferral or refund policy for this program?
Refund Policy: (Programs with/without prep-session component)
- The student must pay applicable caution money for the enrollment of the course. This will be adjustable against the total course fee payable by the student.
- You can claim a refund for the amount paid towards the Program at any time, before the Program Start Date, by visiting www.upgrad.com and submitting your refund form via the "My Application" section under your profile. You can request your Admissions Counsellor to help you in applying and withdrawing for a refund by sending them an email with reasons listed. There shall be no refund applicable once the program has started. This is applicable even for those students who could not complete their payment, and could not be enrolled in the batch opted for. However, the student can avail pre-deferral as per the policy defined below for the same.
- Refund shall be processed to an eligible student within 30 working days from the date of receipt of refund form subject to submission of the right documents from him/her in this regard.
- Refund shall be subject to deduction of USD 150 processing charges and as per the conversion rate applicable.
Deferral Policy: (Post Program Commencement)
- If a student is facing severe issues in dedicating time to the course, we provide the opportunity for the student to defer to another batch. This deferral will be subjected to a 10% deferral fee of the total course amount + taxes if any along with the differential program fees between the two cohorts.
- This deferral request shall be granted only once and to either of the scheduled cohorts to start in the next 1 year from the start date of the initial batch in which the student was originally enrolled for.
- The deferral request will be approved once the deferral fee is paid. Until the process is completed, the student will be assumed to be continuing in the same cohort.
- The student has 7 days (including holidays and weekends) from the date of deferral request to make the payment of the deferral fee post which the deferral request shall be deemed as expired, and the student shall continue as part of the current cohort.
- If the student completes the deferral payment, the student’s login will be disabled, the student will leave the deferred cohort and the student will start learning on the new cohort from the point of the last assignment that was graded in the deferred cohort. All grades and progress till that point will be carried forward as it is to the new cohort. For clarification, the grades of the graded assignments will be carried forward, whether or not the student had submitted these grading during the initial stage.
- The deferral can only be requested during the batch for which the student has enrolled is ongoing. Once the batch has completed, deferral requests shall not be entertained. For clarification, the batch completion here shall mean the “last grace deadline” as communicated by upGrad.
Deferral Policy: (Pre Program Commencement)
- If a student, due to unavoidable circumstances is unable to commence with the cohort and requests for a deferral before the cohort starts, we provide the opportunity for the student to defer to another batch.
- However, the student will be required to pay 50% of the total course fee amount (inclusive of taxes) before the deferral can be approved. Till this is completed, the student will be assumed to be continuing in the same cohort.
- A student can request for deferral only once and to either of the scheduled cohorts to start in the next 1 year from the start date of the initial batch in which the student was originally enrolled for.
- The student shall have time till the current cohort launch date to make the payment of the 50% program fee, post which the deferral request will expire. In the event the student raises a refund request after the deferral window expires, the above-mentioned applicable refund policy shall apply.
- The fee applicable to the deferred student will be as per prevailing fee for the batch student has opted to defer to (No additional deferral fee is required to be paid).The student shall be liable to pay the differential program fees between the two cohorts, if any.
Selection Criteria
What is the selection process for this program?
upGrad, IIITB, world-class faculty, and many industry leaders have committed a lot of time in conceptualising and creating this program to make sure that the candidates can receive the best possible learning experience. Hence, we want to make sure that the participants of this program also show a very high level of commitment and passion for Machine Learning and AI.
The applicants will have to take a 40 minute selection test designed to check their mathematical and programming abilities. The applicants may be exempt from taking the test if they meet the following criteria:
Minimum 1 year of work experience or a degree in Mathematics or Statistics with a particular grade.