Module 4 | Overview: Data Science Using Python
🔊 Turn Data into Insightful Stories
This module helps you unlock the true power of data—by organizing, analyzing, and visualizing it using Python, NumPy, pandas, SQL, and tools like Excel and Tableau. If you’re already familiar with data wrangling and visualization, feel free to move ahead—or use this as a strong recap to sharpen your analytical thinking.
Understanding the Data-Driven World
Learners begin by exploring the basics, types, and evolution of data, along with why data science is crucial in today’s world.Real world applications help them understand how data drives decision-making and innovation.
Building a Statistical Mindset
This section covers the essentials of statistics and probability, including:
• Types of statistics
• Measures of spread and shape
• Outliers and statistical plots
• Predictive insights through probability
• Telling stories with data
These skills strengthen learners' ability to analyze and interpret real datasets.
Python Tools for Practical Data Analysis
Using NumPy, pandas, and Jupyter Notebooks, learners:
• Work with arrays and DataFrames
• Perform indexing, slicing, broadcasting, and calculations
• Import and clean data from CSV, Excel, and JSON files
• Conduct data wrangling and exploratory data analysis (EDA)
These tools are applied in real-world exercises throughout the module.
Exploring the Data Science Workflow
Learners walk through each step of a data science project, including:
• Understanding the workflow and project life cycle
• Working with datasets to clean, analyze, and derive insights
• Presenting findings through structured reports and visual summaries
Data Visualization and Storytelling
Using Google Sheets, Excel, and Tableau, learners:
• Create visual dashboards and charts
• Understand the purpose of visualization
• Use storytelling to communicate insights clearly
• Learn the advantages of different tools
Mastering Databases with SQL
In this final section, learners explore:
• SQL syntax and commands
• Managing databases and using MySQL
• Connecting SQL with Python for data-driven projects
From Raw Data to Real Insights
By the end of the module, learners are ready to handle, analyze, and visualize data with purpose. They gain the skills to transform raw datasets into meaningful insights—preparing them for future work in AI, research, and business analytics.
