About Lesson
- Introduction to machine learning algorithms.
- Supervised and unsupervised learning techniques.
- Model selection and evaluation.
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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