Data Science Fundamentals Online Course

Data Science Fundamentals Online Course

This course is designed to teach you the essential NumPy stack for deep learning, machine learning, and data science. You will gain hands-on experience using NumPy, Matplotlib, Pandas, and SciPy for tasks like numerical computation, data visualization, data manipulation, and basic statistics. The course starts with NumPy to help you understand array operations and complex matrix calculations. Then, you'll explore Matplotlib for data visualization, followed by Pandas for loading and manipulating datasets. Next, you'll dive into SciPy for statistical analysis and conclude with an introduction to machine learning.

By the end, you'll be proficient in using the NumPy stack for data science and deep learning applications.

Who is this course for?

This course is ideal for those interested in data science and machine learning, who already know Python and want to advance their skills with Python libraries for data science. It’s also perfect for anyone looking to gain the tools needed to implement machine learning algorithms. A solid understanding of Python programming, along with a basic knowledge of linear algebra and probability, is required to get the most out of this course.

What you will learn

• Learn supervised machine learning with practical examples
• Code using the NumPy stack for numerical computations
• Implement numerical algorithms with NumPy, SciPy, Matplotlib, and Pandas
• Understand the advantages and disadvantages of different machine learning models
• Get an overview of classification and regression techniques
• Calculate the PDF and CDF for the normal distribution

Course Table of Contents

Welcome and Logistics

• Introduction and Outline
• Course Resources

NumPy

• NumPy Section Introduction
• Arrays Versus Lists
• Dot Product
• Speed Test
• Matrices
• Solving Linear Systems
• Generating Data
• NumPy Exercise
• Where to Learn More NumPy
• Suggestion Box

Matplotlib

• Matplotlib Section Introduction
• Line Chart
• Scatterplot
• Histogram
• Plotting Images
• Matplotlib Exercise
• Where to Learn More Matplotlib

Pandas

• Pandas Section Introduction
• Loading in Data
• Selecting Rows and Columns
• The apply() Function
• Plotting with Pandas
• Pandas Exercise
• Where to Learn More Pandas

SciPy

• SciPy Section Introduction
• PDF and CDF
• Convolution
• SciPy Exercise
• Where to Learn More SciPy

Machine Learning Basics

• Machine Learning: Section Introduction
• What Is Classification?
• Classification in Code
• What Is Regression?
• Regression in Code
• What Is a Feature Vector?
• Machine Learning Is Nothing but Geometry.
• All Data Is the Same
• Comparing Different Machine Learning Models
• Machine Learning and Deep Learning: Future Topics
• Machine Learning: Section Summary