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.
What Will You Learn?
- Types of data: structured, unstructured, and semi-structured, and data quality, preprocessing, and cleaning.
- Advanced data manipulation and analysis using Excel functions, Pivot tables, VLOOKUP, conditional formatting, and data validation.
- SQL queries for data retrieval, manipulation, aggregation, and analysis.
- Introduction to Python and its libraries for data analysis, such as NumPy, pandas, and matplotlib.
- Data exploration and visualization using Python and advanced data analysis techniques with time series data, data aggregation, and group operations.
- Introduction to R and its libraries for data analysis, such as dplyr, ggplot2, and reshape2.
- Data visualization and exploration using data visualization tools, such as Tableau, Power BI, and QlikView.
Audience
This course is suitable for aspiring data analysts, data scientists, business analysts, and professionals looking to enhance their data analytics skills.
Course Content:
Overview of data analytics and its importance in industries
Role of a data analyst
Understanding the data analytics process
Types of data: structured, unstructured, and semi-structured
Data quality, preprocessing, and cleaning
Data exploration and visualization
