You should have a basic understanding of Python programming, including variables, loops, functions, and data structures. No prior data analysis or data science experience is required, but familiarity with basic math and statistics concepts will be helpful.

The course covers the full data analysis lifecycle using Python. You'll master NumPy for numerical computing, Pandas for data wrangling and transformation, Matplotlib and Seaborn for visualization, and explore time series analysis, statistical modeling, regression, and performance optimization techniques.

The course runs for 5 weeks and includes live interactive classes and hands-on projects. You should plan to dedicate approximately 8-10 hours per week, including class time, project work, and practice exercises to get the most out of the curriculum.

You'll work on industry-relevant projects including financial portfolio analysis with NumPy, e-commerce sales data cleaning and reporting with Pandas, customer database integration from multiple sources, time series stock market analysis, and building predictive models — all using real-world datasets.

This course prepares you for roles such as Data Analyst, Business Intelligence Analyst, and aspiring Data Scientist. You'll build a portfolio of hands-on projects demonstrating your ability to wrangle, analyze, visualize, and model data — key skills that employers actively seek in the data analytics job market.

You will work extensively with Python, NumPy, Pandas, Matplotlib, and Seaborn. You'll also learn to read data from multiple sources including CSV, Excel, JSON, SQL databases, and APIs, and apply performance optimization techniques for handling large datasets.

The Micro Degree course is an online LIVE course, where LIVE sessions will be conducted online on our Classroom platform. Prior to the start of the course, you'll receive preparatory material in the form of recorded content which can be access on the same platform.

In this course instructors will use English language for teaching.

Upon successful registration, you will receive a confirmation email on your registered email ID. In this email you will receive login details for your newly created account on the Edyoda Classroom platform (https://classroom.edyoda.com). Additionally, you will receive a PDF guide containing step-by-step instructions on how to utilize the platform to access live sessions and learning materials.

Our instructors are the industry experts with a minimum working experience of 10 years with a strong technical and teaching background. They bring industry knowledge and practical expertise to the course.

Yes, the course includes online assignments, quizzes, and a final project to reinforce your learning and assess your proficiency in Data Analysis Using Python.

Yes, you can interact with instructors and fellow students through discussion forums, live Q&A sessions. We encourage a supportive learning community.

We offer a 100% money-back guarantee to ensure your complete satisfaction. If you're not satisfied, you can request a full refund within 3 days of purchase or before the second session, whichever comes earlier. Simply contact our support team(support@edyoda.com) with your purchase details, such as the order ID or email address, and share your reason for the refund. Requests made after 3 days or after the second session will not be eligible for a refund. There are no hidden charges, you will receive the full amount paid. Refunds are processed within 7–10 business days and credited back to your original payment method.