The Data Analysis with Python is designed to equip learners with the essential skills to analyze, interpret, and visualize data using Python. This course covers the complete data analysis workflow, including data collection, cleaning, exploration, statistical analysis, and visualization. Students will gain hands-on experience with popular Python libraries such as By the end of this course, participants will be able to transform raw data into actionable insights, create interactive visualizations, and make data-driven decisions for real-world business and research applications.
Module 1: Introduction to Python for Data Analysis Overview of Python programming Variables, data types, and operators nConditional statements and loops Functions and basic scripting Setting up Jupyter Notebook/Colab.
Module 2: Data Handling with Pandas Introduction to Pandas DataFrames and Series Importing/exporting data (CSV, Excel, JSON) Data selection, filtering, and indexing Handling missing data and duplicates.
Module 3: Numerical Operations with NumPy Introduction to NumPy arrays Array operations and broadcasting Mathematical and statistical functions Working with large datasets efficiently.
Module 4: Data Cleaning & Preprocessing Handling missing and inconsistent data Data type conversions String manipulation in datasets Feature scaling and normalization.
Module 5: Exploratory Data Analysis (EDA) Descriptive statistics Data aggregation and grouping Correlation and covariance analysis Identifying patterns and outliers.
Module 6: Data Visualization Visualization with Matplotlib and Seaborn Line, bar, scatter, and histogram plots Heatmaps and pairplots Advanced visualization techniques.
Module 7: Statistical Analysis Probability distributions Hypothesis testing t-tests, chi-square tests Regression analysis basics.
Module 8: Working with Real-World Datasets Importing large datasets Data merging, joining, and concatenation Time series analysis and forecasting Case studies from finance, marketing, and healthcare.
Module 9: Automation & Data Reporting Automating repetitive tasks using Python scripts Generating automated reports Data storytelling and presenting insights Integrating Python with Excel and SQL.
Module 10: Capstone Project & Industry Application End-to-end data analysis project Real-world dataset exploration Visualization and reporting of insights Presentation of findings for decision-making.
Mobile: 9100348679
Email: coursedivine@gmail.com
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