1

Introduction to Python for Data Analytics

An overview of Python programming basics and its application in data analysis.

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2

Data Cleaning and Preparation with Pandas

How to use the Pandas library to clean, filter, and transform data for analysis.

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3

Exploratory Data Analysis with NumPy

Techniques for exploring and summarizing data using the NumPy library.

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4

Data Visualization with Matplotlib

Creating various types of visualizations, such as bar charts, scatter plots, and histograms, to communicate data insights effectively.

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5

Statistical Analysis with Python

Performing statistical tests and calculations using Python libraries to derive meaningful insights from data.

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6

Machine Learning Basics with Scikit-Learn

An introduction to machine learning concepts and how to implement basic algorithms for classification and regression tasks.

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7

Time Series Analysis

Techniques for analyzing time series data, including smoothing, decomposition, and forecasting.

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8

Web Scraping and API Integration

Extracting data from websites and APIs using Python to supplement analysis with external datasets.

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9

Case Studies and Real-World Applications

Applying Python skills in data analytics to real-world problems and scenarios to showcase practical use cases.

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