Introduction to Python for Data Science Online Course

Sale price€450.00

We live in an era with an exploding amount of data surrounding us. We can find data in every industry, from agriculture to healthcare, banking to retail, manufacturing to aerospace. To deal with such a massive amount of data, a new field of study named Data Science has emerged to transform data into useful information and insight. Programming is one of the essential skills that data scientists need to learn to implement various algorithms and programs on computers. Python is one of the most widely used programming languages in data science. It is the Swiss Army knife of languages by supporting multiple paradigms, including object-oriented programming (OOP), and with the help of hundreds of specialized libraries that facilitate different functionalities. Python is a dynamic language that is easy to learn and read and thus an optimal choice for beginners.

TechClass Introduction to Python for Data Science online course is designed to introduce you to the basics of the Python programming environment, including fundamental Python programming techniques used in data science. This course gets you acquainted with basic data visualization, manipulation, and exploration techniques using the popular Python data science libraries. Besides, it provides a unique opportunity for you to get hands-on experience with popular Python libraries such as NumPy, Pandas, and Matplotlib. Throughout this course, you will understand the data science workflow and Python programming basics and learn how to take tabular data, clean it, manipulate it, visualize it, and run primary analyses.

Learning outcomes

  • Get familiar with the basics of data science, its workflow, and its challenges
  • Get familiar with the basic concepts of Python
  • Get familiar with the history of Python and why it is important for data science
  • Get familiar with essential Python libraries for data science
  • Learn how to set up a Jupyter Notebook environment and get started using Jupyter Notebooks
  • Get familiar with the basic syntax and rules of writing codes in the Python programming language
  • Learn how to work with different data structures of Python
  • Learn about the concept of functional programming in Python
  • Get familiar with NumPy arrays and why it is important for vector and matrix operations
  • Learn how to use different NumPy functions to operate on arrays
  • Get familiar with the Pandas library, DataFrame, and Series
  • Learn how to work with tabular data and manipulate them
  • Learn how to use the Matplotlib library to produce basic plots of data and results
  • Learn how to plot charts with custom configs and annotations

Table of contents

Chapter 1: Intro to Course 

  • 1.1. Welcome! 
  • 1.2. About TechClass Data Science Department 
  • 1.3. Learning Outcomes 
  • 1.4. Your Expectations, Goals, and Knowledge
  • 1.5. Abbreviations
  • 1.6. Copyright Notice

Chapter 2: Introduction

  • 2.4. What is Data Science?
  • 2.5. Who is a Data Scientist?
  • 2.6. Demand for Data Scientists
  • 2.7. Data Science Workflow
  • 2.8. Data Science Challenges
  • 2.9. Programming in Data Science
  • 2.10. Python for Data Science

Chapter 3: Getting Started with Python

  • 3.1. Jupyter Notebook
  • 3.2. Anaconda
  • 3.3. Anaconda Installation
  • 3.4. Getting Started with Jupyter Notebook
  • 3.5. Python Syntax
  • 3.6. Input and Output
  • 3.7. Variables
  • 3.8. Data Types
  • 3.9. Python Operators
  • 3.10. Arithmetic Operations
  • 3.11. Comparison Operations
  • 3.12. Logical Operations
  • 3.13. String Operations

Chapter 4: Python Data Structures

  • 4.1. Introduction
  • 4.2. List
  • 4.3. List Indexing
  • 4.4. List Slicing
  • 4.5. List Manipulation: Add New Elements
  • 4.6. List Manipulation: Change and Remove Elements
  • 4.7. Tuple
  • 4.8. Accessing Tuple Elements
  • 4.9. Working with Tuples
  • 4.10. Set
  • 4.11. Set Manipulation
  • 4.12. Dictionary
  • 4.13. Accessing Dictionary Elements
  • 4.14. Dictionary Manipulation

Chapter 5: Python Programming Fundamentals

  • 5.1. Conditions: Introduction
  • 5.2. Conditions: if
  • 5.3. Conditions: else
  • 5.4. Conditions: elif
  • 5.5. Loops: Introduction
  • 5.6. Loops: for
  • 5.7. Loops: for in data structures
  • 5.8. Loops: while
  • 5.9. Loops: break, continue
  • 5.10. Functions: Introduction
  • 5.11. Functions: user-defined functions I
  • 5.12. Functions: user-defined functions II
  • 5.13. Comprehensions

Chapter 6: Introduction to NumPy

  • 6.1. Introduction to NumPy
  • 6.2. Array
  • 6.3. Arrays Primary Functions
  • 6.4. Intrinsic NumPy Array Creation
  • 6.5. Creating Random Arrays
  • 6.6. Standard Mathematics Operations
  • 6.7. Broadcasting in NumPy
  • 6.8. Vector and Matrix Mathematics
  • 6.9. Statistics in NumPy
  • 6.10. Common Mathematical Functions
  • 6.11. Comparison and Filtering in NumPy Arrays
  • 6.12. View and Copy

Chapter 7: Data Manipulation with Pandas

  • 7.1. Introduction to Pandas
  • 7.2. Pandas Series
  • 7.3. Pandas DataFrames
  • 7.4. DataFrames: Access Elements
  • 7.5. DataFrames: Insert and Delete
  • 7.6. DataFrames: Concatenate and Merge
  • 7.7. Input and Output: Part 1
  • 7.8. Input and Output: Part 2
  • 7.9. Data Intuition: Summary
  • 7.10. Data Intuition: Statistics
  • 7.11. Data Intuition: Filtering
  • 7.12. Handle Missing Values

Chapter 8: Data Visualization with Matplotlib

  • 8.1. Introduction to Matplotlib
  • 8.2. Plot
  • 8.3. Bar Plot
  • 8.4. Histogram
  • 8.5. Pie Chart
  • 8.6. Scatter Plot
  • 8.7. Plot Attribute
  • 8.8. Subplots

Chapter 9: Final Tasks

  • 9.1. Final Project
  • 9.2. Self-study Essay

Chapter 10: Finishing the Course

  • 10.1. What We Have Learned
  • 10.2. Where to Go Next?
  • 10.3. Your Opinion Matters
  • 10.4. Congrats! You did it!


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Customer Reviews

Based on 6 reviews
Paul Garcia
Comprehensive and fun course

Thank you for this comprehensive Python course. It covers NumPy, Pandas and matplotlib, as well as their important methods.

Chloe Roberts
Good job

Good course for basics of python and intro to Pandas and Numpy.

Alfred Pedersen
Great for beginners with Python

This is a great introduction to Python and data science. It's probably the easiest course in the data science program.

good good good

i am overall happy to take this course, thanks for your efforts

Ella Berglund

The course was really great, and contains important information, and at the same time, it is easy to learn. I gave 4 stars not 5 because I hope in future courses there will be more videos. Overall it was a very nice course, and I love it that TechClass is constantly improving.

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