Introduction to Data Science with Python

About this Course:

This course introduces Python programming as a way to have hands-on experience with Data Science. It starts with a few basic examples in Python before moving onto doing statistical processing. The course then introduces Machine Learning with techniques such as regression classification clustering and density estimation in order to solve various data problems.

Basic knowledge:

This course is for beginners but it helps to have some basic understanding of statistics - mean median scatter plot - and preliminary knowledge of any programming. The course also assumes that you know how to download and install various programs or apps and you are able to edit and debug simple programs.

Course Completion Certificate

What you will learn:

• Writing simple Python scripts to do basic mathematical and logical operations
• Loading structured data in a Python environment for processing
• Creating descriptive statistics and visualizations
• Finding correlations among numerical variables
• Using regression analysis to predict the value of a continuous variable
• Building classification models to organize data into pre-determined classes
• Organizing given data into meaningful clusters
• Applying basic machine learning techniques for solving various data problems

Curriculum:

• Introduction
• Statistical Processing
• Machine Learning with Python

Simpliv LLC, a platform for learning and teaching online courses. We basically focus on online learning which helps to learn business concepts, software technology to develop personal and professional goals through video library by recognized industry experts or trainers.

Why Simpliv

With the ever-evolving industry trends, there is a constant need of the professionally designed learning solutions that deliver key innovations on time and on a budget to achieve long-term success.

Simpliv understands the changing needs and allows the global learners to evaluate their technical abilities by aligning the learnings to key business objectives in order to fill the skills gaps that exist in the various business areas including IT, Marketing, Business Development, and much more.