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Juno Lee,
Andrew Paster,
and
Jennifer Staab
Learn coding with Python, leverage libraries and automation scripts to swiftly solve intricate problems. Enroll in our online Python training for beginners!
Register for this course and see more details by visiting:
OpenCourser.com/course/i62845/introduction
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What's inside
Syllabus
Welcome to Introduction to Python! Here's an overview of the course.
Familiarize yourself with the building blocks of Python! Learn about data types and operators, built-in functions, type conversion, whitespace, and style guidelines.
Read more
Syllabus
Welcome to Introduction to Python! Here's an overview of the course.
Familiarize yourself with the building blocks of Python! Learn about data types and operators, built-in functions, type conversion, whitespace, and style guidelines.
Read more
Use data structures to order and group different data types together! Learn about the types of data structures in Python, along with more useful built-in functions and operators.
Build logic into your code with control flow tools! Learn about conditional statements, repeating code with loops and useful built-in functions, and list comprehensions.
Learn how to use functions to improve and reuse your code! Learn about functions, variable scope, documentation, lambda expressions, iterators, and generators.
Set up your own programming environment to write and run Python scripts locally! Learn good scripting practices, interact with different inputs, and discover awesome tools.
Learn the basics of object-oriented programming so that you can build your own Python package.
In this project, you will use Python code and a created image classifier to identify dog breeds.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Develops foundational skills for becoming a Python developer
Taught by instructors who are recognized for their expertise in Python
занятия курсом не требуют оплаты
Provides hands-on experience through interactive materials
Covers the basics of object-oriented programming, which is a core concept in Python development
Save this course
Save Introduction to Python for AI Programmers to your list so you can find it easily later:
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Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Introduction to Python for AI Programmers with these
activities:
Review Python Fundamentals
Show steps
Refresh your memory on the core concepts and syntax of Python.
Browse courses on
Python Basics
Show steps
-
Review your class materials, including notes and textbooks.
-
Take practice quizzes or tests to assess your understanding.
-
Complete a few coding exercises to reinforce your skills.
Review Fluent Python
Show steps
Understand the best patterns and idioms for writing clear, concise, and efficient Python code.
View
Fluent Python: Clear, Concise, and Effective...
on Amazon
Show steps
-
Read Chapter 1 to 3 to understand the differences between Python 2 and 3.
-
Read Chapter 4 to 6 to learn about idiomatic Python programming.
-
Read Chapter 7 to 9 to learn about more advanced Python features.
Practice Python Coding Challenges
Show steps
Reinforce your understanding of Python syntax and problem-solving skills.
Browse courses on
Python Coding
Show steps
-
Sign up for a coding challenge website or use a resource like HackerRank or LeetCode.
-
Start with easier challenges and gradually increase the difficulty level.
-
Solve at least 5 challenges per week.
One other activity
Expand to see all activities and additional details
Show all four activities
Build a Python Project
Show steps
Apply your Python skills to solve a real-world problem or build a personal project.
Show steps
-
Identify a project idea that interests you and aligns with your learning goals.
-
Plan and design your project, including the features and functionality you want to implement.
-
Implement your project using Python and any necessary libraries or frameworks.
-
Test and debug your project to ensure it works as expected.
-
Document your project with comments and a README file.
Review Python Fundamentals
Show steps
Refresh your memory on the core concepts and syntax of Python.
Browse courses on
Python Basics
Show steps
Show steps
Show steps
- Review your class materials, including notes and textbooks.
- Take practice quizzes or tests to assess your understanding.
- Complete a few coding exercises to reinforce your skills.
Review Fluent Python
Show steps
Understand the best patterns and idioms for writing clear, concise, and efficient Python code.
View
Fluent Python: Clear, Concise, and Effective...
on Amazon
Show steps
Show steps
Show steps
- Read Chapter 1 to 3 to understand the differences between Python 2 and 3.
- Read Chapter 4 to 6 to learn about idiomatic Python programming.
- Read Chapter 7 to 9 to learn about more advanced Python features.
Practice Python Coding Challenges
Show steps
Reinforce your understanding of Python syntax and problem-solving skills.
Browse courses on
Python Coding
Show steps
Show steps
Show steps
- Sign up for a coding challenge website or use a resource like HackerRank or LeetCode.
- Start with easier challenges and gradually increase the difficulty level.
- Solve at least 5 challenges per week.
One other activity
Expand to see all activities and additional details
Show all four activities
Build a Python Project
Show steps
Apply your Python skills to solve a real-world problem or build a personal project.
Show steps
Show steps
Show steps
- Identify a project idea that interests you and aligns with your learning goals.
- Plan and design your project, including the features and functionality you want to implement.
- Implement your project using Python and any necessary libraries or frameworks.
- Test and debug your project to ensure it works as expected.
- Document your project with comments and a README file.
Career center
Learners who complete Introduction to Python for AI Programmers will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
A Data Scientist develops, deploys, and maintains the lifecycle of data-pipelines to solve organization-critical problems, implement real-time analytics, and generate actionable insights. Introduction to Python for AI Programmers can be a stepping-stone into this career by teaching you the basics of Python, a commonly used coding language for data science.
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer designs, develops, deploys, and maintains machine learning models for the organization. Introduction to Python for AI Programmers may be useful because it teaches the basics of Python, a commonly used coding language for machine learning.
Software Developer
Software Developer
A Software Developer designs, develops, deploys, and maintains software systems. Introduction to Python for AI Programmers can be a stepping-stone into this career by teaching you the basics of Python, a commonly used coding language for software development.
Data Analyst
Data Analyst
A Data Analyst prepares, cleans, models, and reports on data to provide insights for decision-making. Introduction to Python for AI Programmers may be useful because Python is a commonly used coding language for data analysis.
Business Intelligence Analyst
Business Intelligence Analyst
A Business Intelligence Analyst analyzes data to provide insights for decision-making. Introduction to Python for AI Programmers may be useful because Python is a commonly used coding language for business intelligence.
Risk Analyst
Risk Analyst
A Risk Analyst identifies, assesses, and mitigates risks. Introduction to Python for AI Programmers may be useful because Python is a commonly used coding language for data science, which is often used for risk analysis.
Statistician
Statistician
A Statistician collects, analyzes, and interprets data to make inferences about a population. Introduction to Python for AI Programmers may be useful because Python is a commonly used coding language for data science, which is a subfield of statistics.
Financial Analyst
Financial Analyst
A Financial Analyst analyzes financial data to make investment decisions. Introduction to Python for AI Programmers may be useful because Python is a commonly used coding language for data science, which is often used for financial analysis.
Quantitative Analyst
Quantitative Analyst
A Quantitative Analyst uses mathematical and statistical modeling to analyze data and make investment decisions. Introduction to Python for AI Programmers may be useful because Python is a commonly used coding language for quantitative analysis.
Actuary
Actuary
An Actuary uses mathematical and statistical modeling to assess risk and make financial decisions. Introduction to Python for AI Programmers may be useful because Python is a commonly used coding language for data science, which is often used for actuarial science.
Computer Programmer
Computer Programmer
A Computer Programmer designs, develops, and implements computer programs. Introduction to Python for AI Programmers can be a stepping-stone into this career by teaching you the basics of Python, a commonly used coding language for computer programming.
IT Project Manager
IT Project Manager
An IT Project Manager plans, executes, and closes IT projects. Introduction to Python for AI Programmers may be useful for learning the basics of coding and project management.
Database Administrator
Database Administrator
A Database Administrator designs, builds, and maintains databases. Introduction to Python for AI Programmers may be useful because Python is a commonly used coding language for data engineering, which is a subfield of database administration.
Data Engineer
Data Engineer
A Data Engineer designs, builds, and maintains data pipelines to support data-driven decision-making. Introduction to Python for AI Programmers may be useful because Python is a commonly used coding language for data engineering.
Systems Analyst
Systems Analyst
A Systems Analyst designs, develops, and implements computer systems. Introduction to Python for AI Programmers can be a stepping-stone into this career by teaching you the basics of Python, a commonly used coding language for systems analysis.
For more career information including salaries, visit:
OpenCourser.com/course/i62845/introduction
Reading list
We've selected 12 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Introduction to Python for AI Programmers.
Provides a comprehensive introduction to Python programming, covering basic concepts, data structures, and control flow. It valuable resource for beginners who want to learn the fundamentals of Python.
Fast-paced, practical introduction to Python programming. It is suitable for beginners who want to learn Python quickly and efficiently.
Save
Uses a visual and interactive approach to teach Python programming. It good choice for beginners who want to learn Python in a fun and engaging way.
Save
Provides a comprehensive introduction to Python programming and computer science. It good choice for beginners who want to learn the fundamentals of Python and computer science.
Save
Teaches Python programming through the lens of computer science. It good choice for beginners who want to learn Python and develop their problem-solving skills.
Provides a comprehensive introduction to Python for data analysis. It covers data structures, data manipulation, and data visualization.
Provides a comprehensive introduction to machine learning with Python. It covers supervised learning, unsupervised learning, and deep learning.
Provides a comprehensive introduction to deep learning with Python. It covers convolutional neural networks, recurrent neural networks, and generative adversarial networks.
Provides a comprehensive introduction to machine learning with Python. It covers supervised learning, unsupervised learning, and deep learning.
Provides a comprehensive introduction to data science with Python. It covers data analysis, data visualization, and machine learning.
Provides a comprehensive introduction to natural language processing with Python. It covers text classification, text clustering, and machine translation.
Provides a comprehensive introduction to Python for finance. It covers data analysis, financial modeling, and risk management.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/i62845/introduction
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Effort
4 weeks
Via
Udacity
Instructors
Juno Lee
Andrew Paster
Jennifer Staab
Language
English
Good to know
Develops foundational skills for becoming a Python developer
Taught by instructors who are recognized for their expertise in Python
занятия курсом не требуют оплаты
Provides hands-on experience through interactive materials
Covers the basics of object-oriented programming, which is a core concept in Python development
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