In this course we teach three major topics
1) Reporting Analytics Tools
2) Business Intelligence Tools
3) Machine Learning with Python
What does this Course Cover?
- Power BI
- Machine Learning
What Will You Learn in the Course?
- Reporting Analytics
- Dashboards Creation
- Data Management
- Data Reporting
- Machine Learning
- Tableau Dashboarding
- Machine Learning Model Building
Key Features of this Course
- 100% hands-on sessions
- Learning through problem-solving and case studies
- Continuous assessments and Feedback
- Multiple Quizzes and Projects
- Access to recorded videos
- Taught by industry professionals with many years of experience in the field
- It contains numerous examples right from the first lecture until the end.
- Every concept is explained using a business scenario or case study.
- It offers the right mix of theory and hands-on labs.
- The course simplifies complex statistical concepts.
- The course offers Python code and a sufficient number of data sets.
- The course is self-sufficient. You do not need any other resource or reference to grasp the concepts.
Target Audience for this Course
- Everybody who wants to get started with machine learning & deep learning
- Reporting analysts who aim to become data scientists.
- Predictive modeling profile candidates who want to learn ML and DL
- Data visualization experts
- Any Data science aspirants
- Graduates and undergraduate students
- Computer Science Engineering students
- There is no strict pre-requisite
- Anyone with a primary degree can get started with this course
- Basic mathematical skills are sufficient
- Statistical Knowledge is NOT a prerequisite. It will be taught in class.
- Cutting-edge programming knowledge is NOT a pre-requisite. Coding will be taught in the class.
- 3 months
- Windows 10 with 8 GB RAM.
- Proxy-free internet, Admin rights to execute scripts
- Firefox and Chrome browsers
Course Delivery Plan
- The training has four major phases in each concept discussion:
- Theory, Demo, in-class exercise, and project assignment.
- The algorithm theory will be explained first. The instructor will take a dataset and demonstrate the concept on a dataset. In the third phase, participants will try the code on a new dataset. In the fourth phase, a real-time dataset will be considered and floated as a project.
|Excel Basic and Advanced|
14 STUDENTS ENROLLED