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.
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Module 2
Collecting data from various sources, including APIs and databases. Cleaning and transforming raw data for analysis. Handling missing data and outliers effectively.
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Module 3
Performing comprehensive exploratory data analysis. Visualizing data with libraries like Matplotlib and Seaborn. Extracting insights and patterns from data.
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Module 4
Creating informative and interactive data visualizations. Building reports and dashboards for data-driven storytelling. Communicating data insights effectively.
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Module 5
Introduction to machine learning concepts and algorithms. Supervised learning, unsupervised learning, and reinforcement learning. Model selection, training, and evaluation.
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Data Science
About Lesson
  • Statistical analysis for data interpretation.
  • Hypothesis testing and confidence intervals.
  • Predictive modeling and regression analysis.