Data Analytics
Overview
Unit 1: Responsible Data Analytics Delve into the ethical considerations of data analytics, understanding legal frameworks, ensuring fairness, and implementing robust data security practices.
Unit 2: Statistics and Mathematics for Data Analysts Master the statistical fundamentals essential for data analysis. Dive into probability, descriptive stats, inferential statistics, regression, and foundational mathematical concepts.
Unit 3: Acquisition and Cleaning With SQL Learn SQL fundamentals, acquire skills for data retrieval and cleaning, explore dataset merging techniques, and advance to proficient SQL practices.
Unit 4: Analysis and Interpretation With Excel Utilize Excel for comprehensive data analysis. Cover essentials for analysis, data visualization, advanced functions, and the power of PivotTables for scenario analysis.
Unit 5: Data Analysis and Communication With Tableau and PowerBI Harness the potential of Tableau and PowerBI for data visualization and storytelling. Create visualizations, interactive dashboards, and learn to integrate these tools for effective data communication.
Unit 6: Data Analysis With Python Discover the capabilities of Python in data analytics. Explore Python fundamentals, data manipulation using Pandas, visualization techniques, and delve into statistical analysis and machine learning.
Unit 7: Data in the Organization Understand data governance, decision-making driven by data, strategies for data integration, and the crucial aspect of data ethics and compliance.
Unit 8: Capstone Projects Apply all learned skills in a comprehensive capstone project, from project planning and data collection to analysis, visualization, and presenting findings for feedback.
Curriculum
**Responsible Data Analytics**
1. Ethical Data Analytics
2. Legal Frameworks and Privacy
3. Bias and Fairness
4. Data Security Best Practices
**Statistics and Mathematics for Data Analysts**
1. Fundamentals of Statistics
2. Probability and Descriptive Stats
3. Inferential Statistics and Regression
4. Mathematical Foundations
**Acquisition and Cleaning With SQL**
1. SQL Fundamentals
2. Data Retrieval and Cleaning
3. Joining Datasets
4. Advanced SQL Techniques
**Analysis and Interpretation With Excel**
1. Excel Essentials for Analysis
2. Data Visualization in Excel
3. Advanced Functions and Analysis
4. PivotTables and What-If Analysis
**Data Analysis and Communication With Tableau and PowerBI**
1. Visualizations in Tableau
2. Interactive Dashboards
3. Data Storytelling
4. Tableau and PowerBI Integration
**Data Analysis With Python**
1. Python Fundamentals
2. Data Manipulation with Pandas
3. Data Visualization in Python
4. Statistical Analysis and Machine Learning
**Data in the Organization**
1. Data Governance and Management
2. Data-Driven Decision Making
3. Data Strategies and Integration
4. Data Ethics and Compliance
**Capstone Projects**
1. Project Planning and Proposal
2. Data Collection and Preparation
3. Analysis and Visualization
4. Presentation and Feedback
