COURSES
- Home
- Courses
- Data Analytics
Data Analytics Course
Step into the dynamic world of Data Analysis by learning the fundamentals, statistical, and various libraries. This course provides both foundational and advanced insights into the world of Data Analysis.
Embark on a rewarding career in Data Analysis by mastering data manipulation, visualization techniques, and statistical methods. This course offers both foundational and advanced knowledge essential for a successful career in data analytics
> Step 1: Practical Projects
2 live projects and 10+ demo projects to build your real-world experience.
> Step 2: Mock Interviews & Placement Support
Comprehensive guidance for preparing for data analyst interviews, along with tips for creating a data-driven resume.
> Step 3: Trainer Expertise
Our trainers are experienced data analysts with industry expertise, offering real-world insights and applications.
- 70 Hours Practical
- 50 Hours Practical
- 120 Total Hours
Dive into the world of Data Analysis by gaining proficiency in data manipulation, visualization techniques, and statistical methods.
- Online Training
- Offline Training
Course Syllabus
Downlaod Syllabus PDF
The Data Analytics course syllabus is designed to provide you with a strong foundation in both theoretical and practical aspects of Data Analytics.
Module 1: Introduction to Data Analysis
- Overview of Data Analysis
- Hello World ProgramRole of a Data Analyst
- Introduction to Data Types
- Data Analysis Process
Module 2: Excel for Data Analysis
- Excel Functions and Formulas
- Data Cleaning
- Pivot Tables
- Data Visualization in Excel
Module 3: SQL for Data Analysis
- Introduction to Databases
- SQL Queries
- Data Extraction
- Joins
- Subqueries
- Aggregation Functions
Module 4: Data Visualization
- Introduction to Data Visualization
- Tools like Tableau/Power BI
- Creating Dashboards
- Best Practices in Visualization
Module 5: Statistics for Data Analysis
- Descriptive Statistics
- Probability
- Hypothesis Testing
- Regression Analysis
- Inferential Statistics
Module 6: Python for Data Analysis
- Introduction to Python
- Libraries like Pandas, NumPy
- Data Wrangling
- Exploratory Data Analysis (EDA)
Module 7: Advanced Excel Techniques
- Advanced Formulas
- VBA for Automation
- Macros
- Complex Data Analysis Techniques in Excel
Module 8: Data Cleaning and Preparation
- Data Cleaning Techniques
- Handling Missing Data
- Data Transformation
- Feature Engineering
Module 9: Case Studies and Projects
- Real-world Data Analysis Projects
- Case Studies
- End-to-End Analysis using Tools and Techniques Learned
Module 10: Data Ethics and Privacy
- Data Governance
- Ethical Considerations in Data Handling
- Data Privacy Regulations
Module 11: Career Preparation
- Resume Building
- Interview Preparation