Post Graduate Programme in Data Science & AI (Executive)

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Post Graduate Programme in Data Science & AI (Executive)

Data Science and AI Executive Program, Post Graduate Program in Data Science & AI, Executive Course in Artificial Intelligence, AI and Data Science Certification, Advanced Data Science Program, AI for Executives

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Requirements

  • bachelor’s degree, Professional Experience, Programming Knowledge, Understanding of Mathematics and Statistics, Analytical and Problem-Solving Skills, Basic Knowledge of AI and Machine Learning

Description

 

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Post Graduate Programme in Data Science & AI (Executive)
Overview
Level-up to data pro with India’s #1 Data Science Programme. Master 14+ tools & languages to earn a WES recognized degree.
Duration 12 Months
Total Fee ₹3,25,000
Mode of learning Online
Difficulty level Beginner
Official Website Go to Our Course
Credential Certificate
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Post Graduate Programme in Data Science & AI (Executive)
Highlights
Discover More
  • 14+ Programming Tools & Languages
  • 60+ Case Studies & 14+ Industry Projects
  • Personalised Industry Session
  • Career Bootcamp
  • No Cost EMI Options Available
  • 1 Free Deferral
  • Up-to-date modules integrated with Generative AI
  • Complimentary Python Programming Bootcamp
  • IIIT Bangalore Alumni Status
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Post Graduate Programme in Data Science & AI (Executive)
Course Details
Skills you will learn
  • Data Analysis, Machine Learning, Python programming, Data Engineering

More about this course
  • Up-to-date Syllabus with Generative AI Modules
  • Complimentary Python Programming Bootcamp
  • 60+ Case studies & 14+ Industry Projects
  • IIIT Bangalore Alumni Status
  • Outcomes of these programs have been audited by Deloitte
  • About 30 weeks of specialized content as per track of choice
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Post Graduate Programme in Data Science & AI (Executive)
Curriculum
Course 1: Data Toolkit
  • Introduction to Python
  • Programming in Python
  • Python for DS
  • Data Visualisation in Python
  • Exploratory Data Analysis
  • Credit EDA Assignment
  • Hypothesis Testing
  • Basics of SQL
  • Advanced SQL
  • SQL - RSVP Movies Case Study
Course 2: Machine Learning - I
  • Linear Regression - I
  • Linear Regression - II + Gradient Descent for SLR
  • Linear Regression Assignment
  • Logistic Regression - I
  • Logistic Regression - II
  • Classification using Decision Trees
  • Unsupervised Learning: Clustering
  • Basics of NLP and Lexical Processing
  • Business Problem Solving + Intro to GIT and GITHUB
  • Case Study: Lead Scoring
Course 3: Data Analytics
  • Data Modelling
  • Advanced SQL Programming
  • Introduction to Cloud and AWS
  • Analytics at Large Scale in Spark - I
  • Analytics at Large Scale in Spark - II
  • Big Data Case Study
  • Basic Viz. using Tableau
  • Advanced Excel
  • Data Analysis and Visualisation in PowerBI
  • Analytical Thinking and Structured Problem Solving using Frameworks
  • Data Storytelling
  • Airbnb Case Study
  • Data Structures and Algorithms
  • Searching & Sorting
  • Algorithm Analysis and Recursion
  • SQL & Python Lab
  • Capstone Topic
Course 4: Business Analytics
  • Bagging & Random Forests
  • Model Selection - I
  • Model Selection - II
  • Time Series Forecasting - I
  • Time Series Forecasting - II
  • Model Selection Case Study
  • Basic Viz. using Tableau
  • Advanced Excel
  • Data Analysis and Visualisation in PowerBI
  • Analytical Thinking and Structured Problem Solving using Frameworks
  • Data Storytelling
  • Airbnb Case Study
  • Operations Research using Excel
  • Introduction to GenAI and Working with OpenAI APIs
  • ChatBot System Design + ShopAssistAI
  • Semantic Searches, Vector Databases, RAG with LlamaIndex
  • Demonstration: PixxelCraftAI
  • Course Project: HelpMateAI+LangChain (optional)
  • Capstone Topic
Course 5: Deep Learning
  • Bagging & Random Forests
  • Boosting
  • Model Selection
  • PCA
  • Advanced Regression + Time Series Forecasting (Optional)
  • Advanced ML Case Study
  • Introduction to Neural Networks and ANN
  • Backpropogation & Hyperparameter Tuning in Neural Networks
  • Introduction to Convolutional Neural Networks
  • CNN Architectures and Industry Applications + Recurrent Neural Networks (Optional)
  • Applications of DL in CV: Object Detection & Image Segmentation (Optional)
  • Gesture Recognition Case Study
  • Attention Mechanism and Transformer Architectures
  • Introduction to GenAI and Working with OpenAI APIs
  • ChatBot System Design + ShopAssistAI
  • Semantic Searches, Vector Databases, RAG with LlamaIndex
  • Diffusion Models + PixxelCraftAI
  • Course Project: HelpMateAI + LangChain (optional)
  • Capstone Topic
Course 6: Natural Language Processing
  • Bagging & Random Forests
  • Boosting
  • Model Selection
  • PCA
  • Advanced Regression + Time Series Forecasting (Optional)
  • Advanced ML Case Study
  • Neural Nets for NLP
  • Syntactic Processing
  • Introduction to Semantic Processing & Distributional Semantics
  • Semantic Processing - Topic Modelling
  • Advanced DL in NLP: Attention Mechanism
  • Automatic Ticket Classification
  • Transformer Architectures and Case Study
  • Introduction to GenAI and Working with OpenAI APIs
  • ChatBot System Design + ShopAssistAI
  • Semantic Searches, Vector Databases, RAG with LlamaIndex
  • LangChain
  • Course Project: HelpMateAI + Demonstration: PixxelCraftAI (optional)
  • Capstone Topic
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Post Graduate Programme in Data Science & AI (Executive)
Entry Requirements
Eligibility Criteria
  • Bachelor's Degree (4 years program) or a Masters Degree in the relevant discipline with at least 55% marks. Minimum of 2 years of work experience

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