Data Science Fundamentals Online Course

Data Science Fundamentals Online Course

This self-paced course introduces the NumPy stack in Python, a key foundation for machine learning, deep learning, and data science. You’ll learn to perform numerical computations with NumPy, visualize data using Matplotlib, manipulate datasets with Pandas, and apply statistical methods with SciPy. The course covers matrix operations, plotting techniques, data frame operations, probability calculations, and statistical testing, along with an introduction to machine learning for classification and regression. By the end, you’ll be able to confidently use the NumPy stack to handle data, perform analysis, and prepare for advanced deep learning projects.

Who should take this Course?

The Data Science Fundamentals Online Course is ideal for students, beginners, and professionals from technical or non-technical backgrounds who want to build a strong foundation in data science concepts. It is also suitable for aspiring data analysts, software developers, and business professionals looking to understand data analysis, visualization, and basic machine learning to make data-driven decisions and enhance their career prospects.

What you will learn

• Understand supervised machine learning with real-world examples
• Understand and code using the NumPy stack
• Make use of NumPy, SciPy, Matplotlib, and Pandas to implement numerical algorithms
• Understand the pros and cons of various machine learning models
• Get a brief introduction to the classification and regression
• Learn how to calculate the PDF and CDF under the normal distribution

Course Outline

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