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- 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
India's #1 Technical University (Private)
Post Graduate Programme in Machine Learning & AI (Executive)
The best selling program with a 4.5 star rating. Learn in-demand skills such as Deep Learning, NLP, MLOps, AI strategy building, work on 15+ industry projects & multiple programming tools.
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TypePG Certificate
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Start DateMay 31, 2024
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Duration13 Months
International Institute of Information Technology, Bangalore
- Advanced AI Lecture Series
- 85+ Countries Learner base
Introduction To PGP In ML & AI From IIIT Bangalore
Course Snapshot
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600+
Hours of Learning
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15+
Industry Projects
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20+
Tools & Libraries
- 20+ Programming and Gen AI tools
- Up to date modules integrated with Generative AI
- Live sessions to cover ChatGPT, Dall-E, Whisper, Pinecone
- 6 Practical Hands-on Capstone Projects
- 1:1 Career Mentorship and High Performance Coaching
- Launch and deploy Generative AI apps
20 Programming Languages, Tools & Libraries Covered
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PG Programme In ML & AI (Executive) Certification
Earn valuable Credentials & Recognition
Complete all the courses successfully to obtain this prestigious recognition from IIIT Bangalore. IIIT Bangalore is one of the Top 70 Engineering Universities as per NIRF Rankings.
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Post Graduate Programme in Machine Learning & AI (Executive)
- 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
Explore Our Learning Platform
Learn on an AI-powered & personalised platform with best-in-class
content, live sessions & mentoring from leading industry experts.
Syllabus Of IIIT-B PG In ML & AI
What will you learn?
Experience 600+ hours of best-in-class content developed by leading faculty & industry leaders in the form of videos, case studies & projects
600+ Hours of Learning
15+ Case Studies and Assignments
35+ Live Sessions
6 Capstone Projects to Choose From
Stats and EDA
4 Weeks
Topics (5)
- EDA + Welcome
- Intro to Git & Github
- Lending club case study
- Inferential Stats
- Hypothesis Testing
Machine Learning - I
- 7 Weeks
Topics (6)
- Linear Regression Module
- Linear Regression Assignment:Bike sharing company(demand regression)
- Logistic Regression
- Naive Bayes
- Model Selection
- Revision week - Skill test
Machine Learning - II
- 9 Weeks
Topics (9)
- Advanced Regression
- Advance regression assignment + SVM (Optional)
- Tree Models
- Random Forests + Practical Considerations
- Boosting - 1
- Unsupervised Clustering
- PCA
- Telecom Churn Case Study
- Buffer - Skill test
Deep Learning
- 9 Weeks
Topics (9)
- Introduction to Neural Networks - Part1
- Introduction to Neural Networks - Part2
- Convolutional Neural Networks
- Assignment: Convolutional Neural Networks
- CNN : Practical Considerations
- Recurrent Neural Networks
- Gesture Recognition - Project
- Exam on Sunday End of the week
- Revision week - Skill test (DL)
Natural Language Processing
- 7 Weeks
Topics (6)
- NLP - Lexical Processing
- NLP - Syntactic Processing
- NLP Assignment - Syntactic Processing
- NLP - Semantic Processing
- Buffer - Skill test(NLP)
- Ticket classification Project
ELective : MLops ELective
- 10 Weeks
Topics (14)
- Pre-Requisite Module
- Introduction to MLops
- Designing Machine Learning Systems
- Experimenting with Data and Model using MLflow
- Automating and Orchestrating piepelines with Airflow
- Building continuous learning infrastructure
- MLOps Project
- Advanced NLP - Introduction to Attention Mechanism
- Advanced NLP - Introduction to Transformers
- Advanced CV - Object Detection & Semantic Segmentation
- MLOps + Deployment: DL (Theory)
- MLOps + Deployment: DL (Case Study)
- Exam on Sunday End of the week
- Revision week - Skill test
Elective : Generative AI Elective
- 15 Weeks
Topics (15)
- Advanced NLP - Introduction to Attention Mechanism
- Advanced NLP - Introduction to Transformers
- "Fundamentals of Generative AI, ChatGPT & Prompt Engineering using Non Reasoning, Chain of Thought & Advanced Techniques"
- Product Development using OpenAI APIs, Fine Tuning using STaR technique in Python
- Integrating speech using Whisper API and application deployment using Flask
- Fundamentals of Multimodal LLMS like Stable Diffusion, Mid Journey
- "Fundamentals of Design, Photography & Product Development using Stable Diffusion in Python & Applications of LLMs for Data Science problems like clustering, classification"
- GenAI Project
- Applications of LLMs to create Embeddings for Large Documents
- Applications of Vectorstores like Pinecone to store and index embeddings of large documents
- Understand the importance of LangChain and it's applications
- Initialise the agents, tools and vectorstore for storage and retrieval
- Connect the components using Chain and explore the power of tools in LangChain
- Scale and Deploy Generative AI Apps using Azure OpenAI services
- Future Developments in Generative AI
INSTRUCTORS
Whom will you learn from?
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20 Instructors
Chandrashekar Ramanathan
Dean - Academics-
Prof. Chandrashekar has a Ph.D. from Mississippi State University and experience of over 10 years in several multinational organizations.
Prof. Chandrashekar has a Ph.D. from Mississippi State University and experience of over 10 years in several multinational organizations.
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S. Anand
- CEO
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A Gold medalist from IIM Bangalore, an alumnus of IIT Madras and London School of Business, Anand is among the top 10 data scientists in India.
A Gold medalist from IIM Bangalore, an alumnus of IIT Madras and London School of Business, Anand is among the top 10 data scientists in India.
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Ujjyaini Mitra
- Head of Analytics
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An alumnus of McKinsey and Co., Flipkart, and Bharti Airtel with over 11 years of experience.
An alumnus of McKinsey and Co., Flipkart, and Bharti Airtel with over 11 years of experience.
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Prof. S. Sadagopan
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- Director, IIITB
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Prof. Sadagopan is currently Director (President) of IIITB. He has a MS and a PhD from Purdue University.
Prof. Sadagopan is currently Director (President) of IIITB. He has a MS and a PhD from Purdue University.
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Anshuman Gupta
- Director | Data Science
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He has a Ph.D. (Dual) from Penn State University as well as a B.Tech. Degree from IIT Bombay.
He has a Ph.D. (Dual) from Penn State University as well as a B.Tech. Degree from IIT Bombay.
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Prof. G. Srinivasaraghavan
- Professor
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Prof. Srinivasaraghavan has a Ph.D. in Computer Science from IIT Kanpur and 18 years of experience with Infosys Technologies.
Prof. Srinivasaraghavan has a Ph.D. in Computer Science from IIT Kanpur and 18 years of experience with Infosys Technologies.
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Dinesh Babu Jayagopi
- Asst. Prof.
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Prof. Dinesh has a Ph.D. from Ecole Polytechnic Federate Switzerland, M.Sc. from IISc Bangalore in System Science and Signal Processing, and B.Tech.
Prof. Dinesh has a Ph.D. from Ecole Polytechnic Federate Switzerland, M.Sc. from IISc Bangalore in System Science and Signal Processing, and B.Tech.
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Kalpana Subbaramappa
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- Ex-AVP
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Kalpana is the ex-AVP of Decision Sciences at Genpact with over 20 years of experience.
Kalpana is the ex-AVP of Decision Sciences at Genpact with over 20 years of experience.
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Srinath Srinivasa
- Professor & Dean | R&D
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He holds a Ph.D. in Information Systems from the Berlin-Brandenburg Graduate School, Germany, and is a recipient of various international grants.
He holds a Ph.D. in Information Systems from the Berlin-Brandenburg Graduate School, Germany, and is a recipient of various international grants.
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Mirza Rahim Baig
- Lead | Business Analytics
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Advanced analytics professional with 8+ years of experience as a consultant in the e-commerce and healthcare domains.
Advanced analytics professional with 8+ years of experience as a consultant in the e-commerce and healthcare domains.
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Chandramouleeswaran
- Adjunct Faculty at IIIT Bangalore
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He has 33+ years of experience in networking, embedded SW, ML. He is an Adjunct faculty at IIIT Bangalore and a visiting faculty at IIIT Lucknow.
He has 33+ years of experience in networking, embedded SW, ML. He is an Adjunct faculty at IIIT Bangalore and a visiting faculty at IIIT Lucknow.
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Georgios Ouzounis
- Head of ML Engineering
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Technologist and visionary with over 22 years of experience and serving as the head of ML Engineering at Atlas AI in California, USA
Technologist and visionary with over 22 years of experience and serving as the head of ML Engineering at Atlas AI in California, USA
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Arihant Jain
- Head of Data Science & Risk
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Arihant is an expert in the field of Machine Learning technologies and is currently heading Data Science and Risk at IIFL Finance
Arihant is an expert in the field of Machine Learning technologies and is currently heading Data Science and Risk at IIFL Finance
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Usha Rengaraju
- Chief of Research
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She hails from the prestigious Harvard as well as Columbia University. She is a unicorn data scientist and have over 10 years of industry experience
She hails from the prestigious Harvard as well as Columbia University. She is a unicorn data scientist and have over 10 years of industry experience
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Snehansu Sekhar Sahu
- Applied Scientist
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Snehansu is currently working as an applied scientist at Amazon . Prior to Amazon Snehansu was the Senior AI Researcher in ML & AI for Amex.
Snehansu is currently working as an applied scientist at Amazon . Prior to Amazon Snehansu was the Senior AI Researcher in ML & AI for Amex.
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Chiranjoy Chowdhuri
- Chief Analytics Officer
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Chiranjoy is a Data, Analytics and AI practitioner with 13 years’ experience and In his current role, he is the Global Head of Data and Analytics at Pidilite Industries
Chiranjoy is a Data, Analytics and AI practitioner with 13 years’ experience and In his current role, he is the Global Head of Data and Analytics at Pidilite Industries
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Sajan Kedia
- Machine Learning Lead
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Sajan has extensive experience in the field of ML, Big Data, Data Science, and AI. He is the Machine learning lead at Myntra
Sajan has extensive experience in the field of ML, Big Data, Data Science, and AI. He is the Machine learning lead at Myntra
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Ankit Jain
- Sr. Research Scientist
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An alumnus of IIT Bombay, UCB and Harvard Business School with over 9 years of experience
An alumnus of IIT Bombay, UCB and Harvard Business School with over 9 years of experience
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Rohit Ghosh
- Founding Member & Chief Strategy Officer
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Rohit is a IIT-Bombay grad and currently Founding Member & Chief Strategy Officer of Qure.ai
Rohit is a IIT-Bombay grad and currently Founding Member & Chief Strategy Officer of Qure.ai
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Gunjan Narulkar
- Director, AI/ML Product R&D
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Gunjan has extensive experience in the AI- Ml products and R&D and is currently working as a director at Fidelity Investments.
Gunjan has extensive experience in the AI- Ml products and R&D and is currently working as a director at Fidelity Investments.
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PG In AI & ML Related Projects
Learn by Doing
Gain industry exposure with relevant projects taught by leading faculty from IIIT Bangalore AI ML department and industry leaders.
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15+ Industry Projects
Credit EDA Assignment
In this PG Diploma in AI project, you will work for a consumer finance company that specialises in lending various types of loans to urban customers and use EDA to analyse the patterns in the data. This will ensure that the applicants are capable of repaying the loan and are not rejected.
In this PG Diploma in AI project, you will work for a consumer finance company that specialises in lending various types of loans to urban customers and use EDA to analyse the patterns in the data. This will ensure that the applicants are capable of repaying the loan and are not rejected.
Skills learned
- Data Cleaning
- Data Visualisation
- Data Analysis
- Data Interpretation
Model Selection Case Study -Telecom Churn
As a business analyst, I've been tasked with helping a telecom company combat customer churn, a major pain point in the competitive telecom industry. To achieve this, I propose a data-driven approach that leverages the power of Masters in Artificial Intelligence and Machine Learning.
As a business analyst, I've been tasked with helping a telecom company combat customer churn, a major pain point in the competitive telecom industry. To achieve this, I propose a data-driven approach that leverages the power of Masters in Artificial Intelligence and Machine Learning.
Skills learned
- Logistic Regression
- Tree Models
- Model Selection
- Feature Engineering
- Classification
- MSc Artificial Intelligence and Machine Learning
- Model Evaluation
- Business Problem Solving
Advanced ML Case Study - Telecom Churn
Telecom companies operate in a fiercely competitive landscape like artificial intelligence and machine learning masters, constantly grappling with the challenge of customer churn. A data scientist can play a critical role in identifying churn-prone customers and devising data-driven strategies to retain them, ultimately boosting customer lifetime value and improving profitability.
Telecom companies operate in a fiercely competitive landscape like artificial intelligence and machine learning masters, constantly grappling with the challenge of customer churn. A data scientist can play a critical role in identifying churn-prone customers and devising data-driven strategies to retain them, ultimately boosting customer lifetime value and improving profitability.
Skills learned
- Logistic Regression
- Tree Models
- Boosting
- Model Selection
- Regularization
- Feature Engineering
- Classification
- MS in Machine Learning and Artificial Intelligence
- Model Evaluation
- Business Problem Solving
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Lending Club Case Study
In this assignment, you will work for a consumer finance company which specialises in lending various types of loans to urban customers and use EDA to analyse the patterns present in the data. This will ensure that the applicants are capable of repaying the loan and are not rejected.
In this assignment, you will work for a consumer finance company which specialises in lending various types of loans to urban customers and use EDA to analyse the patterns present in the data. This will ensure that the applicants are capable of repaying the loan and are not rejected.
Skills learned
- Data Cleaning
- Data Visualisation
- Data Analysis
- Data Interpretation
Bike Sharing Assignment
Build a regression model to understand the factors on which the demand for bike sharing systems vary on and help a company optimise its revenue.
Build a regression model to understand the factors on which the demand for bike sharing systems vary on and help a company optimise its revenue.
Skills learned
- Data Cleaning
- Data Visualisation
- Data Analysis
- Data Interpretation
- Linear Regression
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Advanced Regression Assignment
Build a regularized regression model to understand the most important variables to predict housing prices in a US market
Build a regularized regression model to understand the most important variables to predict housing prices in a US market
Skills learned
- Data Cleaning
- Data Visualisation
- Data Analysis
- Data Interpretation
- Generalized Linear Regression
- Regularization
- Hyperparameter Tuning
Melanoma Detection Assignment
Build a custom convolutional neural network neural network from scratch in Tensorflow to identify the type of skin cancer from image.
Build a custom convolutional neural network neural network from scratch in Tensorflow to identify the type of skin cancer from image.
Skills learned
- Data Understanding
- Data Visualization
- Convolutional Neural Network
- Model Building and Training
- Data Augmentation
- Class Imbalance
- Model Evaluation
Gesture Recognition Project
Make a Smart TV system which can control the TV with user’s hand gestures as the remote control.
Make a Smart TV system which can control the TV with user’s hand gestures as the remote control.
Skills learned
- Data Understanding
- 3D Convs
- CNN-RNN
- Generator Functions
- Model Building and Training
- Model Tuning
- Model Evaluation
Custom Entity detection in Healthcare data
Build a custom NER to get the list of diseases and their treatment from a medical healthcare dataset.
Build a custom NER to get the list of diseases and their treatment from a medical healthcare dataset.
Skills learned
- Regular expressions
- Text cleaning
- Bag-of-Words model
- TF-IDF
- Model building
- PoS tagging
- Parsing
- NER
- Custom NER and CRF
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
Create a solution that will help in identifying the type of complaint ticket raised by the customers of a multinational bank
Skills learned
- Data Cleaning
- Data Preprocessing
- Data Visualisation
- Feature Extraction
- Topic Modelling
- Model Building
- Model Inference
Lead Scoring
Build an end-to-end MLOps pipeline for an edtech company to identify customers most likely to convert and streamline the overall lead conversion process
Build an end-to-end MLOps pipeline for an edtech company to identify customers most likely to convert and streamline the overall lead conversion process
Skills learned
- Pycaret
- MLflow
- Data Ingestion Pipeline
- Model Training Pipeline
- Model Inference Pipeline
Style Transfer using GAN's
Build a Model for converting MRI images from one type (T1) into other (T2) and vice versa.
Build a Model for converting MRI images from one type (T1) into other (T2) and vice versa.
Skills learned
- Custom model building
- Model tuning
- Data cleaning and wrangling
- EDA and visualisation
- Generative Adversarial Network (GAN)
- CycleGAN
- ML Modelling
- Model Evaluation
- Business Problem Solving
Sales Forecasting
Help an European pharma giant accurately forecast sales at their individual stores
Help an European pharma giant accurately forecast sales at their individual stores
Skills learned
- Data Understanding
- Data Preparation
- Time Series Analysis - ARIMA, SARIMA, VAR, VARMAX
- Model evaluation
Eye for the Blind
Build a model that can help any visually impaired person in understanding image present before them.
Build a model that can help any visually impaired person in understanding image present before them.
Skills learned
- Computer vision
- Image captioning
- Text to speech
- CNN-RNN based architecture
- Attention model
- Custom model building using Tensorflow
- Data preparation using Tensorflow
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.
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.
Skills learned
- Data preparation
- Lexical Processing
- ML Model building
- Recommender System
- Model evaluation
- Model deployment
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.
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.
Skills learned
- Data Preparation
- Collaborative Filtering
- Content-based Filtering
- Hybrid Recommender System
- Exploratory data analysis
- Machine learning
- Model building
- Model evaluation
AI Mastery Syllabus
Dive into the latest trends like ChatGPT, Dall E, and Explainable AI (XAI) through this series by renowned experts in the field.
The GPT-3 Revolution
- Introduction to ChatGPT: The world of AI is constantly evolving, and staying up to date with the latest advancements can be challenging. This session will introduce you to the power and potential of GPT-3.
- Objective: To comprehensively understand GPT-3, its capabilities like Natural Language Understanding(NLU) & Context Recognition, and how it can be used in their work or business.
Be 10x productive with Prompt Engineering
- Prompt engineering is a powerful technique that can help content creators, freelancers, and businesses generate high-quality text quickly and efficiently. This session will introduce you to the concept of prompt engineering and its applications.
- Objective: The objective of this session is to provide learners with a comprehensive understanding of prompt engineering and how it can be used with different AI tools like ChatGPT3, Midjourney & Stable Diffusion.
- By the end of the session, learners will be able to use prompt engineering techniques to generate high-quality text for a variety of applications.
From Black Box to Glass Box: An Introduction to Explainable AI
- With the increasing adoption of AI, there is a growing need to ensure that AI models can be understood and trusted. This session will introduce you to the concept of Explainable AI and Model Interpretability.
- Objective: To gain a comprehensive understanding of the importance of XAI (Explainable Artificial Intelligence) and model interpretability, and learn how to build and interpret an interpretable machine learning model using LIME & SHAP techniques
Is AI racist and biased?
- As AI is increasingly used in various domains, it is important to consider the ethical implications and potential biases that can arise. This session will introduce learners to the concepts of ethics and bias in AI and provide real-world examples.
- Objective: To understand the ethical and bias considerations in AI and how to identify and mitigate potential issues. Learn through case studies in healthcare, finance, autonomous vehicles, recruitment among others.
From Data to Dialogue: Diving into ChatGPT's Architecture and Functionality
- This session will provide an overview of GPT models and their architecture, along with advanced techniques like RLHF and InstructGPT.
- Objective: The objective of this session is to introduce learners to one of the variant of the Transformer - the GPT model, specifically the Davinci variant. They will gain knowledge about the architecture of GPT models and advanced techniques such as Reinforcement Learning from Human Feedback (RLHF), one-shot & few shot learning. They will also learn how to fine-tune GPT models with prompts and evaluate their performance through hands-on exercises.
ChatGPT-Based Ticket Classifier: A Game-Changer for Support Teams
- Using transfer learning with GPT-3 eliminates the need to train NLP models from scratch, and provides access to state-of-the-art language models on various NLP tasks. This session will help you perform 'Ticket Classification Using ChatGPT'
- Objective: To build a product that can automatically classify support tickets into different categories based on their topics using the fine-tuned ChatGPT model. This will help companies and organizations to improve their support ticket handling efficiency and reduce the workload of their support teams.
Build an Image generator using Stable Diffusion
- Using transfer learning with GPT-3 eliminates the need to train NLP models from scratch, and provides access to state-of-the-art language models on various NLP tasks. This session will help you 'Build an image generator using stable diffusion'
- Objective: The objective of this session is to teach learners how to build an image generator using Stable Diffusion and the Hugging Face library. They will learn how to prepare data, build and train a Stable Diffusion model, evaluate its performance, and build a Streamlit dashboard to showcase the model's output.
The World of Graph Networks
- This session aims to simplify the process and provide learners with a comprehensive understanding of Graph Neural Networks (GNNs) and how to build a simple GNN model.
- Objective: The objective of this session is to introduce learners to the components of a GNN, its working mechanism, and how to build a simple GNN model for a given problem statement. By the end of the session, learners will be able to apply their knowledge to solve problems related to graph data.
Advanced Graph Networks
- With the limitations of simple GNNs, there is a need to explore advanced GNN architectures. This session aims to provide an in-depth understanding of advanced graph networks.
- Objective: By the end of this session, learners should be able to comprehend the drawbacks of simple GNNs. Additionally, learners should be able to compare and evaluate the performance of advanced GNNs like Graph Convolutional Networks(GATs) & Graph Attention Networks(GANs) to simple GNNs
State of Art (STOA) architectures in Computer vision
- In this session, we will introduce learners to the concept of landmark and feature detection, and enable them to build a simple landmark detection system.
- Objective: By the end of the session, learners will be able to understand the fundamentals of landmark detection, popular feature detection algorithms such as SIFT and SURF, and build a landmark detection system using feature detection algorithms.
State of Art(STOA) architectures in generative modelling
- Keeping up with the latest advancements in generative modeling can be challenging. This session aims to provide an overview of the state-of-the-art (STOA) architectures in generative modeling and their applications.
- Objective: By the end of the session, learners should have an understanding of the STOA architectures in generative modeling and be able to read research papers on topics such as image-to-text models (Vision Transformers), text-to-image models(CoCA, CLIP), and multimodality(Pathways).
2 minPG In AI And ML Learner Services
How will upGrad support you?
360 Degree Career Support services, Personalized Mentorship from Industry Experts, Hands-on Projects, Peer Networking opportunities & a whole lot more to help you master Machine Learning & AI.
Student Support
- Student Support available all day for your convenience (24*7)
- For urgent queries, use the Call Back option on the platform
Networking & Learning Experience
- Live Discussion forum for peer to peer doubt resolution monitored by technical experts
- Peer to peer networking opportunities with a alumni pool of 10000+
- Lab walkthroughs of industry-driven projects
- Weekly real-time doubt clearing sessions
High Performance Coaching (1:1)
- Get a dedicated career coach after the program to help track your career goals, coach you on your profile, and support you during your career transition journey
AI Powered Profile Builder
- Obtain specific, AI powered inputs on your resume and Linkedin structure along with content on real time basis
Interview Preparation
- Get access to Industry Experts and discuss any queries before your interview
- Career bootcamps to refresh your technical concepts and improve your soft skills
Career Impact
Personalised Industry Session
Sessions by an industry expert for a small group of 10-12 learners with similar profiles to discuss real life applications of concepts and personalised coaching.
High Performance Coaching (1:1)
Get a dedicated career coach to help you stay on track to achieve your career goals, coach you on your profile, and support you in your career journey.
Interview Preparation
Support in polishing your hard skills and soft skills for interview preparation.
Our Learners upGrad alumni Work At
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Success stories
What Our Learners Say
Updated with the latest industry practices and trends
My transformative journey with upGrad has been nothing short of remarkable. The program provided me with a comprehensive learning experience that equipped me with the latest tools and skills used in the industry. From design to publishing, I learned how to navigate through every stage of a project efficiently.One aspect that particularly impressed me was the platform itself. It's user-friendly and constantly evolving based on student feedback, ensuring that we have access to the best resources and learning materials available. The live classes conducted by industry professionals were invaluable, keeping me updated with the latest industry practices and trends.Overall, I am extremely satisfied with what I've learned through upGrad. It's not just about acquiring knowledge but also about connecting with professionals and building a network that will be beneficial for my career growth. I am truly grateful for the opportunity to be a part of this transformative journey with upGrad.
My transformative journey with upGrad has been nothing short of remarkable. The program provided me with a comprehensive learning experience that equipped me with the latest tools and skills used in the industry. From design to publishing, I learned how to navigate through every stage of a project efficiently.One aspect that particularly impressed me was the platform itself. It's user-friendly and constantly evolving based on student feedback, ensuring that we have access to the best resources and learning materials available. The live classes conducted by industry professionals were invaluable, keeping me updated with the latest industry practices and trends.Overall, I am extremely satisfied with what I've learned through upGrad. It's not just about acquiring knowledge but also about connecting with professionals and building a network that will be beneficial for my career growth. I am truly grateful for the opportunity to be a part of this transformative journey with upGrad.
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Cassandra Pratt Romero
- Software Engineer at Microsoft
- 6 Years of Experience
The urge to upskill myself led me to join this program
The urge to upskill myself led me to join this program. The program has been really great and has instilled a sense of confidence in me. The idea that i am part of something that is going to bring a revolution in near future is incredible. Post upGrad, i plan to continue my journey into the vast ocean of Artifical Intelligence and make a good name for myself.
The urge to upskill myself led me to join this program. The program has been really great and has instilled a sense of confidence in me. The idea that i am part of something that is going to bring a revolution in near future is incredible. Post upGrad, i plan to continue my journey into the vast ocean of Artifical Intelligence and make a good name for myself.
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Atul Chauhan
- Applied Controls Engineer at Daikin
- 8 Years of Experience
The progress in AI and ML in the last decade sparked my curiosity about this topic
The progress in AI and ML in the last decade sparked my curiosity about this topic. The UpGrad program looked well planned and built, with a reasonable price. The offline mode of education allowed me to study and learn while working at my job. During my learning journey with upGrad, I reinforced and learned new concepts I plan to use in my daily life and professional career. In the future, I will continue working and learning about these topics and applying them to my jobs.
The progress in AI and ML in the last decade sparked my curiosity about this topic. The UpGrad program looked well planned and built, with a reasonable price. The offline mode of education allowed me to study and learn while working at my job. During my learning journey with upGrad, I reinforced and learned new concepts I plan to use in my daily life and professional career. In the future, I will continue working and learning about these topics and applying them to my jobs.
Read More
Jheser Guzman Illanes
- Vice President of Software Engineering at JPMorgan Chase & Co.
- 18 Years of Experience
It was a fantastic journey so far with the support of UpGrad team
I wanted to get into the ML\AI space for some time and decided to enroll in UpGrad after being inspired by a friend. It was a fantastic journey so far with the support of UpGrad team (special kudos to Karen for the excellent job) and I never imagined that I can make this far as I am a pretty occupied individual personally as well as professionally. I am looking forward to complete my masters and pursue PhD in near future. The foundation provided was fabulous and has enabled me to do design some innovative solutions at work. Thanks to UpGrad for making it happen.
I wanted to get into the ML\AI space for some time and decided to enroll in UpGrad after being inspired by a friend. It was a fantastic journey so far with the support of UpGrad team (special kudos to Karen for the excellent job) and I never imagined that I can make this far as I am a pretty occupied individual personally as well as professionally. I am looking forward to complete my masters and pursue PhD in near future. The foundation provided was fabulous and has enabled me to do design some innovative solutions at work. Thanks to UpGrad for making it happen.
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Vsmy Naresh Kumar Kuppili
- Solution Architect at Image Access Corp
- 11 Years of Experience
Eligibility Of PG In AI And ML Course
How to Apply
The Executive PG Diploma in Machine Learning & Artificial Intelligence admissions process is easy and can be done entirely online.
Eligibility
Bachelor’s Degree with 50% or equivalent passing marks. Minimum 1 year of work experience in a technical domain or a degree in mathematics or Statistics with programming experience
Online Eligibility Test
Fill out an application and take a quick 40-minute online test with 18 questions to assess your aptitude.10 questions from mathematics, aptitude & reasoning & 8 questions from programming.
Fill out an application and take a quick 40-minute online test with 18 questions to assess your aptitude.10 questions from mathematics, aptitude & reasoning & 8 questions from programming.
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Review & Shortlisting of Suitable Candidates
Our faculty will review all applications, considering the educational & professional background of an applicant, review the test scores where applicable. Following this, Offer Letters will be rolled out so you are assured a great peer group to learn & network with.
Our faculty will review all applications, considering the educational & professional background of an applicant, review the test scores where applicable. Following this, Offer Letters will be rolled out so you are assured a great peer group to learn & network with.
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Enrollment for Access to Prep Content
Make a quick block payment with assistance from our loan partners where required, receive immediate access to the prep content and begin your upGrad journey.
Make a quick block payment with assistance from our loan partners where required, receive immediate access to the prep content and begin your upGrad journey.
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Program Fees: USD 3,999
Refer someone you know and receive cash reimbursements of up to $500!*
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*More details under the referral policy under Support Section
upGrad Learner Support
Monday - Friday | 9:30 am to 7:30 pm SGT.
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*If we are unavailable to attend to your call, it is deemed that we have your consent to contact you in response.