• Basics of Python Programming Language.
• Basic knowledge about Supervised Machine Learning.

This course addresses the huge demand for data scientists and covers each stage of the entire data science project lifecycle. You will learn how to collect, clean, and store data into a data warehouse as well as perform Exploratory Data Analysis (EDA) on the collected data using statistical and graphical analysis.

Then onwards, this course will guide you through a six-stage Machine Learning workflow aimed at creating powerful and robust data models from scratch. This course will also take you through the process of deploying the created data model into production using a fast, simple, and extensible Web API framework called Flask.

By the end of this course, you will leave with the necessary skills to make your next data science project a reality.

• Engineer data pipelines using the ETL process.
• Perform statistical and graphical analysis.
• Execute a 6-stage Machine Learning (ML) workflow.
• Deploy data models into a production environment using Web APIs.

• Updated 2021 course content: All our course content is updated as per the latest technologies and tools available in the market
• Practical hands-on knowledge: This course is oriented to providing a step-by-step implementation guide rather than just sticking to the theory.
• Guided support: We are always there to guide you through the Q/As so feel free to ask us your queries.

Any beginner, intermediate, or expert developer looking to upskill as a full-stack data scientist.

• Lifetime Access to course updates
• Fast & Friendly Support in the Q&A section