Course Content
Module 1
Understanding the role of data science in today's world. Exploring the data science workflow and methodologies. Introducing key data science tools and languages.
Module 2
Collecting data from various sources, including APIs and databases. Cleaning and transforming raw data for analysis. Handling missing data and outliers effectively.
Module 3
Performing comprehensive exploratory data analysis. Visualizing data with libraries like Matplotlib and Seaborn. Extracting insights and patterns from data.
Module 4
Creating informative and interactive data visualizations. Building reports and dashboards for data-driven storytelling. Communicating data insights effectively.
Module 5
Introduction to machine learning concepts and algorithms. Supervised learning, unsupervised learning, and reinforcement learning. Model selection, training, and evaluation.
Data Science
About Lesson
  • Collecting, cleaning, and formatting data.
  • Exploratory data analysis (EDA) techniques.
  • Data visualization for insights.