Data Analytics Masterclass
This comprehensive 20-session course covers essential concepts, tools, and best practices for data analytics, with each session lasting 2 hours. The course will guide you through various data analytics techniques, tools, and technologies, as well as their practical application in real-world projects. You will also work on a hands-on demo project that simulates real-world industry scenarios, enabling you to apply the skills learned throughout the course.
About Course
This comprehensive 20-session course is designed to provide you with the skills and knowledge required to excel as a data analyst. Each session lasts 2 hours, and the course covers key concepts, tools, and best practices for data analytics, as well as their practical application in real-world projects. The curriculum includes a hands-on industry demo project that simulates real-world scenarios, enabling you to apply the skills learned throughout the course.
In the last three sessions, you will work on a hands-on demo project that simulates real-world industry scenarios. The project aims to provide practical experience in designing, implementing, and evaluating data analytics solutions for a given business problem. The project will help you gain a deep understanding of the data analytics process, allowing you to apply the skills and knowledge acquired throughout the course to real-world industry projects.
No, prior experience in data analytics or programming is not required. The course starts with the fundamentals of data analytics, making it accessible to beginners. However, some basic knowledge of statistics and programming would be helpful.
- This course is suitable for aspiring data analysts, data scientists, business analysts, and professionals looking to enhance their data analytics skills.
The hands-on demo project is designed to give you practical experience in working with real-world industry scenarios. You will work on a data analytics project from start to finish, including data collection and preprocessing, analysis, visualization, and interpretation of results. The project helps you apply the concepts and techniques you have learned throughout the course, ensuring you gain the skills needed to work on real-world industry projects.
- While there are no strict prerequisites, some basic knowledge of statistics and programming would be helpful to get the most out of the course.
This course covers a wide range of data analytics topics and techniques, which may be helpful in preparing for various data analytics-related certifications. However, the course is not specifically designed to prepare you for a particular certification exam. If you’re interested in pursuing a certification, it’s a good idea to identify the specific exam you’d like to take and review its requirements, then use this course as a foundation and supplement it with additional study materials and practice exams as needed.
By the end of this course, you will have gained a solid understanding of data analytics concepts and tools, as well as their practical application in real-world industry scenarios. You will also have completed a hands-on demo project that simulates real-world industry scenarios, which will enable you to apply your newly acquired skills and knowledge to solve complex business problems.
Course Content
Session 1: Introduction to Data Analytics
Overview of data analytics and its importance in industries
Role of a data analyst
Understanding the data analytics process
Session 2: Data Fundamentals
Session 3: Introduction to Excel for Data Analytics
Session 4: Advanced Excel Techniques
Session 5: SQL for Data Analytics
Session 6: Introduction to Python for Data Analytics
Session 7: Advanced Python Data Analysis Techniques
Session 8: Introduction to R for Data Analytics
Session 9: Advanced R Data Analysis Techniques
Session 10: Descriptive Statistics
Session 11: Inferential Statistics
Session 12: Introduction to Machine Learning
Session 13: Advanced Machine Learning Techniques
Session 14: Data Warehousing and ETL
Session 15: Big Data Analytics
Session 16: Data Visualization Tools
Session 17: Data Analytics Project Management
Session 18: Real-World Industry Project – Part 1
Session 19: Real-World Industry Project – Part 2
Session 20: Real-World Industry Project – Part 3
