Course Summary
Learn how to apply Python programming skills to real-world data science and AI projects in this comprehensive course. Gain hands-on experience with popular data science libraries and tools, and learn to analyze and visualize data to make informed decisions.Key Learning Points
- Learn to use Python for data science and AI projects
- Gain hands-on experience with popular data science libraries and tools
- Develop skills in data analysis and visualization
Related Topics for further study
Learning Outcomes
- Apply Python skills to real-world data science and AI projects
- Develop proficiency in popular data science libraries and tools
- Analyze and visualize data to make informed decisions
Prerequisites or good to have knowledge before taking this course
- Basic knowledge of programming concepts
- Familiarity with Python programming language recommended
Course Difficulty Level
IntermediateCourse Format
- Online
- Self-paced
Similar Courses
- Applied Data Science with Python
- Python Data Science Handbook
Related Education Paths
Related Books
Description
Kickstart your learning of Python for data science, as well as programming in general, with this beginner-friendly introduction to Python. Python is one of the world’s most popular programming languages, and there has never been greater demand for professionals with the ability to apply Python fundamentals to drive business solutions across industries.
Knowledge
- Build your first program in Python
- Learn about Python fundamentals, Python data structures, and working with data in Python
- Become familiar with key Python functions, objects, and classes
- Gain career skills in one of the world’s most popular programming languages
Outline
- Python Basics
- Types
- Expressions and Variables
- String Operations
- About this course
- Practice Quiz
- Practice Quiz
- Practice Quiz
- Module 1 Graded Quiz
- Python Data Structures
- List and Tuples
- Dictionaries
- Sets
- Practice Quiz
- Practice Quiz
- Practice Quiz
- Module 2 Graded Quiz
- Python Programming Fundamentals
- Conditions and Branching
- Loops
- Functions
- Exception Handling
- Objects and Classes
- Practice Quiz
- Practice Quiz
- Practice Quiz
- Practice Quiz
- Practice Quiz
- Module 3 Graded Quiz
- Working with Data in Python
- Reading Files with Open
- Writing Files with Open
- Loading Data with Pandas
- Pandas: Working with and Saving Data
- One Dimensional Numpy
- Two Dimensional Numpy
- Practice Quiz
- Practice Quiz
- Practice Quiz
- Module 4 Graded Quiz
- APIs, and Data Collection
- Simple APIs (Part 1)
- Simple APIs (Part 2)
- REST APIs & HTTP Requests - Part 1
- REST APIs & HTTP Requests - Part 2
- Optional: HTML for Webscraping
- Webscraping
- Working with different file formats (csv, xml, json, xlsx)
- Next Steps
- Python Cheat Sheet: The Basics
- Practice Quiz
- Practice Quiz
- Module 5 Graded Quiz
- Final Exam
Summary of User Reviews
Discover how to use Python for applied data science and AI with this comprehensive course on Coursera. Users have praised the course for its engaging content, practical approach, and great instructors. Many have found the course to be an excellent resource for learning Python and its applications in data science and AI.Key Aspect Users Liked About This Course
The course content is engaging and practical, making it an excellent resource for learning Python and its applications in data science and AI.Pros from User Reviews
- Engaging content that keeps users interested and motivated
- Practical approach that focuses on real-world scenarios and applications
- Great instructors who are knowledgeable and supportive
- Excellent resource for learning Python and its applications in data science and AI
Cons from User Reviews
- Some users may find the pace of the course too slow or too fast, depending on their level of experience
- The course may require a significant time commitment, particularly for those who are new to Python and data science
- Some users have reported technical issues with the course platform or materials
- The course may not be suitable for users who are looking for a more theoretical or academic approach to data science and AI