Data Science and Analytics

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Data Science combines statistics, programming, and domain expertise to extract meaningful insights from data. This course introduces you to the fundamentals of data analysis, visualization, and machine learning, enabling you to solve real-world problems using data-driven approaches. Whether you want to become a data analyst, data engineer, or machine learning practitioner, this course provides the essential skills and tools.

You’ll work hands-on with Python, Jupyter Notebooks, Pandas, NumPy, Matplotlib, Scikit-learn, and SQL. The course includes projects in data cleaning, exploratory data analysis, visualization, and predictive modeling. By the end, you’ll be able to analyze complex datasets, build machine learning models, and communicate results effectively.

Course Modules

Module 1

  • Introduction to Data Science and Its Applications
  • Overview of Data Types and Data Collection
  • Python for Data Science: Basics and Setup
  • Jupyter Notebooks and Data Exploration
  • Hands-On Lab: Python Data Analysis Basics

Module 2

  • Data Wrangling and Cleaning with Pandas
  • Working with Missing Data and Outliers
  • Data Transformation and Feature Engineering
  • Data Visualization with Matplotlib and Seaborn
  • Hands-On Lab: Exploratory Data Analysis (EDA)

Module 3

  • Introduction to Statistics for Data Science
  • Probability Distributions and Hypothesis Testing
  • Correlation, Regression, and Statistical Inference
  • SQL for Data Science: Querying Databases
  • Hands-On Lab: Statistical Analysis and SQL Queries

Module 4

  • Introduction to Machine Learning Concepts
  • Supervised Learning: Regression and Classification
  • Unsupervised Learning: Clustering and Dimensionality Reduction
  • Model Evaluation and Validation Techniques
  • Hands-On Lab: Build and Evaluate ML Models

Module 5

  • Deploying Data Science Models
  • Introduction to Big Data and Cloud Platforms
  • Data Science Project Workflow and Best Practices
  • Communication and Data Storytelling
  • Final Project: End-to-End Data Science Solution
  • Submit: Data Science Capstone Project

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