Data Analysis Diploma - Technical Proposal
Module 1
Introduction to Data Analysis (4 hours)
- Fundamentals of Data Analysis
- Types of Data (Structured vs. Unstructured)
- Overview of the Data Analysis Workflow
- Industry Applications of Data Analysis
Module 2
Python for Data Analysis (8 hours)
- Python Basics (Variables, Data Types, Control Flow)
- Working with Lists, Tuples, and Dictionaries
- Functions and Modules in Python
- Introduction to Libraries: NumPy & Pandas
- Data Manipulation and Transformation using Pandas
- Handling Missing Data
Module 3
SQL and Databases (6 hours)
- Introduction to Databases and SQL
- Data Retrieval with SELECT Statements
- Filtering, Aggregation, and Joins
- Subqueries and Common Table Expressions (CTEs)
- Data Cleaning and Manipulation in SQL
Module 4
Exploratory Data Analysis (EDA) (6 hours)
- Understanding Descriptive Statistics
- Data Visualization with Matplotlib & Seaborn
- Identifying Outliers and Anomalies
- Feature Engineering and Selection
- Data Correlation and Relationships
Module 5
Data Cleaning and Preprocessing (6 hours)
- Handling Duplicates and Missing Data
- Standardization and Normalization
- Encoding Categorical Data
- Feature Engineering for Better Analysis
- Handling Large Datasets Efficiently
Module 6
Data Visualization with Power BI & Tableau (8 hours)
- Introduction to Business Intelligence Tools
- Power BI:
- Data Modeling in Power BI
- Creating Interactive Dashboards
- Using DAX for Advanced Calculations
- Connecting Power BI with SQL and Python
- Tableau:
- Introduction to Tableau Environment
- Data Connections & Data Blending
- Building Interactive Visualizations
- Advanced Charts & Filters
- Creating Dynamic Dashboards
Module 7
Statistical Analysis and Hypothesis Testing (6 hours)
- Understanding Probability Distributions
- Statistical Inference and Hypothesis Testing
- ANOVA and Chi-Square Testing
- Regression Analysis: Linear & Logistic
- Time Series Analysis Basics
Module 8
Final Project & Case Study (4 hours)
- End-to-End Data Analysis Project
- Working with Real-World Datasets
- Generating Insights and Building Reports
- Presenting Data Findings with Dashboards (Power BI & Tableau)
Tools & Technologies Covered
- Programming: Python (NumPy, Pandas, Matplotlib, Seaborn)
- Databases: SQL (PostgreSQL / MySQL)
- Business Intelligence: Power BI, Tableau
- Statistics & Analysis: SciPy, StatsModels
Outcome
By the end of this diploma, you will have hands-on experience in data analysis, SQL, Python programming, visualization with Power BI & Tableau, and statistical techniques—fully preparing you for real-world data analyst roles.
