What You'll Learn
- Master Microsoft Excel for data analysis, pivot tables, and advanced formulas
- Write SQL queries for data extraction, joins, aggregations, and database management
- Perform statistical analysis including descriptive statistics, probability, and distributions
- Conduct hypothesis testing, ANOVA, chi-square tests, and correlation analysis
- Learn regression analysis (linear, multiple, logistic) for predictive modeling
- Use Python libraries: Pandas for data manipulation, NumPy for numerical computing
- Create stunning visualizations with Matplotlib, Seaborn, and Plotly
- Build interactive dashboards and reports using Power BI and Tableau
- Master data cleaning techniques: handling missing values, outliers, and duplicates
- Perform exploratory data analysis (EDA) and feature engineering
- Apply time series analysis and forecasting methods
- Work with real-world datasets from business, finance, and e-commerce domains
- Create professional data reports and presentations for stakeholders
- Implement A/B testing and experimental design
- Use statistical tools like Goal Seek, Solver, and Scenario Manager in Excel
- Complete 15+ industry-relevant projects including sales analysis, customer segmentation, and business intelligence dashboards
About This Course
This comprehensive data analyst course covers everything you need to become a professional data analyst from scratch. Master Excel for data analysis and visualization, learn SQL for database querying and management, Python (Pandas, NumPy, Matplotlib) for advanced analytics, and statistical methods for hypothesis testing, regression, and predictive modeling. You'll work with Power BI and Tableau for creating interactive dashboards, perform data cleaning and transformation, and apply descriptive and inferential statistics. Through 15+ hands-on projects using real-world datasets, you'll learn to extract insights, create compelling visualizations, and make data-driven business decisions. Perfect for beginners and professionals looking to transition into the high-demand field of data analytics.
Course Curriculum
0 sections • 0 lessons
Course curriculum will be added soon.
Requirements
- No prior experience in data analysis or programming required
- Basic computer skills and familiarity with Windows/Mac operating system
- Microsoft Excel installed (2016 or later version recommended)
- A computer with minimum 4GB RAM and stable internet connection
- Basic mathematics knowledge (high school level)
- Willingness to learn statistics and coding fundamentals
- 8-10 hours per week commitment for hands-on practice
- Python and SQL installation guides provided in the course
- Interest in working with data and solving analytical problems
Instructor
emo
Professional Instructor
- Lifetime access
- Access on mobile and desktop
- Certificate of completion
- 0 lessons