Description

Course Description:

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.

Key Features of Course Divine:

• Collaboration with E‑Cell IIT Tirupati
• 1:1 Online Mentorship Platform
• Credit-Based Certification
• Live Classes Led by Industry Experts
• Live, Real-World Projects
• 100% Placement Support
• Potential Interview Training
• Resume-Building Activities

 Career Opportunities After  Data Analysis with Python Certified Course:

• Data Analyst
• Business Intelligence (BI) Analyst
• Data Scientist (Entry-Level)
• Python Developer for Data Analysis
• Financial Analyst
• Market Research Analyst
• Operations Analyst
• Research Analyst
• Healthcare Data Analyst
• Data Visualization Specialist

Essential Skills you will Develop Data Analysis with Python Certified Course:

• Python Programming Fundamentals
• Data Cleaning & Preprocessing
• Data Exploration & Analysis
• Data Visualization
• Working with Pandas & NumPy
• Statistical Analysis
• Handling Real-World Datasets
• Time Series Analysis
• Data Aggregation & Grouping
• Data-Driven Decision Making

Tools Covered:

• Python
• Jupyter Notebook / JupyterLab
• Pandas
• NumPy
• Matplotlib
• Seaborn
• Plotly
• SciPy
• OpenPyXL / xlrd
• SQL / SQLite

Syllabus:

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.

Industry Projects:

• Sales Data Analysis Project
• Customer Segmentation Project
• Financial Data Analysis Project
• Healthcare Data Analysis Project
• Marketing Campaign Analysis Project
• Employee Performance & HR Analytics Project
• E-commerce Data Analysis Project

Who is this program for?

• Aspiring Data Analysts
• Students & Graduates
• Working Professionals
• Business & Marketing Analysts
• Researchers & Academics
• Python Enthusiasts
• Career Switchers
• Entrepreneurs & Startups

How To Apply:

Mobile: 9100348679

Email: coursedivine@gmail.com