Data Analytics Course
This comprehensive Data Analytics program is designed to equip you with the job-ready skills needed to become a successful data analyst. You will journey through data foundations, advanced spreadsheet techniques, database querying with SQL, data manipulation with Python, and storytelling with data visualization tools like Tableau or Power BI. The course is packed with real-world case studies and culminates in a capstone project to build your professional portfolio.
Weekly Syllabus
Weeks Module 1
Introduction to Data Analysis: What is data analysis & why it matters, Types of data, Data analyst roles, Data analysis lifecycle, Real-world use cases.
Weeks Module 2
Data Foundations: Data types, scales of measurement, Data quality issues, Data ethics & privacy basics, Introduction to databases.
Weeks Module 3
Excel / Spreadsheets for Data Analysis: Data cleaning & formatting, Formulas & functions (VLOOKUP/XLOOKUP, IF, etc.), Pivot tables & charts, Basic dashboards.
Weeks Module 4
SQL for Data Analysis: Database concepts, SELECT, WHERE, ORDER BY, Aggregations, Joins, Subqueries, Working with real datasets.
Weeks Module 5
Python for Data Analysis: Python basics, NumPy, Pandas (cleaning, manipulation), Data visualization (Matplotlib, Seaborn).
Weeks Module 6
Data Cleaning & Wrangling: Handling missing data, Outliers & duplicates, Data transformation, Feature engineering basics.
Weeks Module 7
Exploratory Data Analysis (EDA): Descriptive statistics, Data distributions, Correlation analysis, Pattern & trend discovery, Hypothesis generation.
Weeks Module 8
Data Visualization & Storytelling: Best practices, Choosing the right chart, Dashboard design (Tableau/Power BI), Communicating insights.
Weeks Module 9
Statistics for Data Analysis: Probability basics, Descriptive vs inferential statistics, Sampling, Hypothesis testing, Regression basics.
Weeks Module 10
Business & Decision Analytics: KPIs & metrics, A/B testing, Forecasting basics, Data-driven decision making.
Weeks Module 11
Capstone Project: End-to-end data analysis project from problem definition to presentation.
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