In this practical, hands-on course, you’ll learn how to program using Python for Data Science and Machine Learning, including data analysis, visualization, and how to use data practically.

The course objective is to understand the ins and outs of the Python programming language for Data Science and Machine Learning and learn the importance of Data Science and Python.  In addition, we’ll go over the best and most essential Python libraries for data science such as NumPy, Pandas, and Matplotlib +

NumPy — A library that makes a variety of mathematical and statistical operations easier; it is also the basis for many features of the pandas library.

Pandas — A Python library created specifically to facilitate working with data; this is the bread and butter of a lot of Python data science work.

NumPy and Pandas are great for exploring and playing with data. Matplotlib is a data visualization library that makes graphs as you’d find in Excel or Google Sheets. Blending practical work with solid theoretical training, we take you from the basics of Python Programming for Data Science to mastery.

This Machine Learning with Python course dives into the basics of machine learning using Python. You’ll learn about supervised vs. unsupervised learning, look into how statistical modeling relates to machine learning, and make a comparison of each.

Understand that theory is essential to build a solid foundation, understand that theory alone isn’t going to get the job done, so that’s why this course is packed with practical hands-on examples that you can follow step by step. Even if you already have some coding experience or want to learn about the advanced features of the Python programming language.

Python coding experience is required or recommended in job postings for data scientists, machine learning engineers, big data engineers, IT specialists, database developers, and much more. In addition, adding Python coding language skills to your resume will help you in any data specializations requiring mastery of statistical techniques.

Get an understanding of how to write code in Python, analyze and visualize data, and utilize machine learning algorithms.

You will learn:

PYTHON FOR DS+ML

• • Intro to Data Science + Machine Learning with Python
  • Data Science Industry and Marketplace
  • Data Science Job Opportunities
  • How To Get a Data Science Job
  • Machine Learning Concepts & Algorithms

PYTHON DATA ANALYSIS/VISUALIZATION

• • Python Crash Course
  • NumPy Data Analysis
  • Pandas Data Analysis

MATHEMATICS FOR DATA SCIENCE

• • Descriptive Statistics
  • Measure of Variability
  • Inferential Statistics
  • Probability
  • Hypothesis Testing

MACHINE LEARNING

• • Intro to Machine Learning
  • Data Preprocessing
  • Linear Regression
  • Logistic Regression
  • K-Nearest Neighbors
  • Decision Trees
  • Ensemble Learning
  • Support Vector Machines
  • K-Means Clustering
  • PCA