- Foundations of Data Science
Introduction to Data Science Data Science Life Cycle Applications of Data Science
- Foundations of Statistics
Basic Concepts of Statistics Probability Theory Statistical Inference
- Data Sources and Types
Types of Data Data Sources Data Storage Technologies
- Programming Skills for Data Science
Introduction to Python for Data Science Introduction to R for Data Science
- Data Wrangling and Preprocessing
Data Imputation Techniques Handling Outliers and Data Transformation
- Exploratory Data Analysis (EDA)
Introduction to EDA Data Visualization
- Generative AI Tools for Deriving Insights
Introduction to Generative AI Tools Applications of Generative AI
- Machine Learning
Introduction to Supervised Learning Algorithms Introduction to Unsupervised Learning Different Algorithms for Clustering Association Rule Learning with Implementation
- Advance Machine Learning
Ensemble Learning Techniques Dimensionality Reduction Advanced Optimization Techniques
- Data-Driven Decision-Making
Introduction to Data-Driven Decision Making Open Source Tools for Data-Driven Decision Making Deriving Data-Driven Insights from Sales Dataset
- Data Storytelling
Understanding the Power of Data Storytelling Identifying Use Cases and Business Relevance Crafting Compelling Narratives Visualizing Data for Impact
- Capstone Project - Employee Attrition Prediction
Project Introduction and Problem Statement Data Collection and Preparation Data Analysis and Modeling Data Storytelling and Presentation
- Foundations of Data Science
Introduction to Data Science Data Science Life Cycle Applications of Data Science
- Foundations of Statistics
Basic Concepts of Statistics Probability Theory Statistical Inference
- Data Sources and Types
Types of Data Data Sources Data Storage Technologies
- Programming Skills for Data Science
Introduction to Python for Data Science Introduction to R for Data Science
- Data Wrangling and Preprocessing
Data Imputation Techniques Handling Outliers and Data Transformation
- Exploratory Data Analysis (EDA)
Introduction to EDA Data Visualization
- Generative AI Tools for Deriving Insights
Introduction to Generative AI Tools Applications of Generative AI
- Machine Learning
Introduction to Supervised Learning Algorithms Introduction to Unsupervised Learning Different Algorithms for Clustering Association Rule Learning with Implementation
- Advance Machine Learning
Ensemble Learning Techniques Dimensionality Reduction Advanced Optimization Techniques
- Data-Driven Decision-Making
Introduction to Data-Driven Decision Making Open Source Tools for Data-Driven Decision Making Deriving Data-Driven Insights from Sales Dataset
- Data Storytelling
Understanding the Power of Data Storytelling Identifying Use Cases and Business Relevance Crafting Compelling Narratives Visualizing Data for Impact
- Capstone Project - Employee Attrition Prediction
Project Introduction and Problem Statement Data Collection and Preparation Data Analysis and Modeling Data Storytelling and Presentation
, Optional Module: AI Agents for Data Analysis, Foundations of Data Science, Foundations of Statistics, Data Sources and Types, Programming Skills for Data Science, Data Wrangling and Preprocessing, Exploratory Data Analysis (EDA), Generative AI Tools for Deriving Insights, Machine Learning, Advance Machine Learning, Data-Driven Decision-Making, Data Storytelling, Capstone Project - Employee Attrition Prediction
Download Overview