You should have basic Python programming knowledge, including familiarity with variables, loops, functions, and data structures. No prior data science or machine learning experience is required—the course builds these skills from the ground up.

The curriculum covers data analysis fundamentals with NumPy, data wrangling and transformation with Pandas, time series analysis, exploratory data analysis (EDA) techniques, data visualization with Matplotlib and Seaborn, handling multiple data formats (CSV, Excel, JSON, SQL), and building predictive models. You'll work with real-world financial, e-commerce, and customer datasets throughout.

This is a 12-week program. You should plan to dedicate approximately 8-10 hours per week, including video lessons, reading materials, coding exercises, and hands-on project work. The structured schedule allows working professionals to balance learning with their current roles.

The course is highly practical. Each chapter includes hands-on exercises such as financial data analysis, e-commerce dataset cleaning, customer database integration, and stock market time series manipulation. You'll also complete three capstone projects that simulate real industry scenarios, building a portfolio you can showcase to employers.

Completing this course prepares you for roles such as Data Analyst, Data Scientist, Business Intelligence Analyst, and Machine Learning Engineer. You'll gain industry-relevant skills in Python-based data analysis, visualization, and predictive modeling that are in high demand across finance, e-commerce, healthcare, and technology sectors.

You'll work extensively with Python and its core data science libraries: NumPy for numerical computing, Pandas for data manipulation, Matplotlib and Seaborn for visualization, and Scikit-learn for machine learning. You'll also learn to read data from multiple formats including CSV, Excel, JSON, and SQL databases.

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 Science 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.