
Hi everyone! I'm Merishna, a data scientist at The Click Reader and welcome to this course on Full-Stack Data Science with Python.
Instructions on how to open the coding exercises.
Learn the basics of Data Engineering along with the Extract-Transform-Load (ETL) process.
Learn the basics of web scraping along with a coding exercise in Python.
Perform data extraction using Web Scraping and Python.
Learn how to transform the extracted data.
Load the data into a database/data warehouse.
Learn the introductory concepts of Exploratory Data Analysis (EDA).
Learn how to perform Statistical Analysis as a part of the EDA process.
Learn how to perform Graphical Analysis as a part of the EDA process.
Perform EDA on the weather report dataset.
Learn the fundamental concepts for performing Data Modeling using Machine Learning.
Learn the basic concepts of Dependent and Independent variables.
Learn the 6-stage Machine Learning workflow.
Learn how to perform data pre-processing for Machine Learning.
Learn how to perform data splitting for Machine Learning.
Build and train a Machine Learning model.
Learn how to evaluate Machine Learning models.
Learn how to deploy Machine Learning models for production.
Learn the basic concepts of using Web APIs for model deployment.
Congratulations on completing all the lessons of this course!
Link to additional learning materials.
Get educated and obtain the skills necessary as a Data Scientist to engineer, analyze, build, and deploy intelligent Machine Learning models in this immersive, Full Stack Data Science Course created by The Click Reader.
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.
Why you should take this course?
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.