About the Course
Data science is an exciting field that blends statistics, computer science, and domain knowledge to extract meaningful insights from data. This course will equip you with the skills to analyze, visualize, and interpret data, opening doors to countless opportunities in various industries.
Module 1: Introduction to Data Science
Week 1: What is Data Science?
Understanding the Role of a Data Scientist
Overview of the Data Science Process
Key Concepts and Terminology
Week 2: Tools and Technologies in Data Science
Introduction to Programming (Python Focus)
Introduction to Data Analysis Tools (e.g., Jupyter Notebooks)
Basic SQL for Data Retrieval
Module 2: Statistical Foundations for Data Science
Week 3: Descriptive Statistics
Measures of Central Tendency and Variability
Data Distributions and Summary Statistics
Week 4: Inferential Statistics
Probability Concepts
Hypothesis Testing and p-Values
Correlation vs. Causation
Module 3: Data Manipulation and Analysis
Week 5: Data Manipulation using Pandas
Introduction to Pandas Library
Data Cleaning and Preparation
Week 6: Exploratory Data Analysis (EDA)
Visualization with Matplotlib and Seaborn
Understanding Data Through Visualization
Module 4: Introduction to Machine Learning
Week 7: Basics of Machine Learning
Types of Machine Learning: Supervised, Unsupervised, and Reinforcement Learning
Simple Linear Regression and Logistic Regression
Week 8: Machine Learning Project
End-to-End Project from Data Preprocessing to Model Building
Evaluating Model Performance
Your Instructor
Experienced trainers from MNC
Experienced trainers from MNC
