Python required for Data Science and Machine Learning 2020

Basic Python, Data Analysis & Insights Visualizations. Case Study. High level Machine Learning lib & tools walk through.

What you'll learn

Hands on skills in Data Insights Visualization
Collections - List, Set, Dictionaries, Tuples
Pandas DataFrames - Intruduction and Operations and more
Matrix Operations
Multidimensional Arrays
Case Study to visualize meaningful insights
High level walk through of Machine Learning tools
Visual plots such as line, bar, scatter, histogram etc.
Seaborn for basic visualizations to retrieve meaningful insights
Matplotlib for basic visualizations to retrieve meaningful insights
Installing anaconda and Launching jupyter
Fundamentals of programming such as Decision Controls, Loops, Operators, Data types etc.
Creating Identifiers, Operators
and more !

Requirements

No programming knowledge required. I'll teach you.
You just need computer or mobile phone with internet connection to access course material.
Course also covers fundamentals of programming such as Decision Controls, Loops, Operators, Data types and more so that beginners also can understand.

Description

Lets learn basics to transform your career.

I promise not to exhaust you with huge number of videos.

Welcome to the most comprehensive Python required for Data Science and Machine Learning course! An excellent choice for beginners and professionals looking to up skill themselves in the domain of Machine Learning and Data Science. This course of First Step or prerequisite to learn Machine Learning or Data Science. This course covers most popular Python libraries in the world such as collections, numerical pyhton, matplotlib, seaborn and pandas data frames. This course includes case study for drawing meaningful insights out of given business data.

Course also covers most fundamentals of programming such as Decision Controls, Loops, Operators, Data types and more !

Going forward, every software development would be AI or Data Driven and students or professional needs to have respective skills to adapt themselves in the changing industry. Since Machine Learning and Data Science are hot in today's market and students or professionals needs to re-skill or up-skill themselves to AI or Machine Learning or Data Science to survive in today's market.

This course of First Step or prerequisite to learn Machine Learning or Data Science.


Python required for Data Science and Machine Learning course offers video tutorials on exact python required to get yourself started with Machine Learning and Data Science.

Numerical Python is a powerful library which efficiently performs matrix operations faster and exceed the python capabilities of data processing.

Pandas is a powerhouse tool that allows you to do anything and everything with tabular or columnar data sets – analyzing, organizing, sorting, filtering, aggregating, cleaning, calculating, and more!

Matplotlib is an amazing visualization library in Python for 2D plots of arrays. Matplotlib is a multi-platform data visualization library built on NumPy arrays. One of the greatest benefits of visualization is that it allows us visual access to huge amounts of data in easily digestible visuals. Matplotlib consists of several plots like line, bar, scatter, histogram etc.

Seaborn is a library for making statistical graphics in Python. It is built on top of matplotlib and closely integrated with pandas data structures.

Whether you're a new data analyst, planning to transit yourself to data analyst role or have spent years in Excel, this course offers you an incredible introduction to one of the most powerful data tool kits available today!

Who this course is for:

Anyone who want to start with Basic Python required for Machine Learning and Data Science in short period of time.
Anyone who want to up skill then into Machine Learning and Data Science. This course is First Step
Managers who want to up skill them for high paying data jobs
Production Support Engineers who want to up skill them
Beginner python developer curious about data visualization
Data analysts, Business Analysts