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Our Python for Beginners course will introduce you to core programming concepts and fundamental Python syntax by writing code to make a virtual "turtle" robot draw colorful shapes.
Register for this course and see more details by visiting:
OpenCourser.com/course/ndmlil/programming
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What's inside
Syllabus
Get started learning core programming concepts with Python, while writing instructions to make a virtual "turtle" robot draw colorful shapes on the screen.
Learn how to use Python loops to iterate over data and run code repeatedly.
Learn how to write compound statements and functions, and use them to control the flow of execution in your Python code.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Suitable for beginners, it can aid learners in establishing a basic foundation in Python
Practical in nature, it can help learners apply Python to create visual representations using a virtual 'turtle' robot
Covers essential Python concepts, including loops, compound statements, and functions
Save this course
Save Programming with Python Fluency 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 Programming with Python Fluency with these
activities:
Review Python Basics
Show steps
By reviewing the fundamentals of Python syntax and programming concepts, you'll strengthen your understanding of the upcoming lessons.
Browse courses on
Python Syntax
Show steps
-
Refer to online tutorials or documentation to recap Python syntax.
-
Revisit basic programming concepts, such as variables, data types, and operators.
-
Complete practice problems to test your understanding.
Explore Python Functions
Show steps
By exploring guided tutorials on Python functions, you'll gain a deeper understanding of how to define, call, and utilize functions to structure and modularize your code effectively.
Show steps
-
Search for online tutorials or documentation that cover Python functions.
-
Follow along with the tutorials, practicing the creation and implementation of functions.
-
Experiment with different function parameters and return values.
-
Apply your knowledge to real-world coding scenarios.
Collaborative Python Coding
Show steps
Engaging in collaborative Python coding sessions with peers will allow you to share knowledge, troubleshoot problems, and reinforce your understanding of the course material.
Show steps
-
Connect with classmates or online communities to form study groups.
-
Choose a specific topic or project to work on together.
-
Regularly meet to discuss ideas, solve problems, and provide feedback.
-
Utilize collaborative coding tools or platforms to work on projects together.
Three other activities
Expand to see all activities and additional details
Show all six activities
Design a Python Project
Show steps
Designing a Python project will provide you with hands-on experience in applying the concepts learned in the course, fostering a deeper understanding of Python programming.
Show steps
-
Brainstorm project ideas that align with your interests and course objectives.
-
Outline the project's goals, scope, and functionality.
-
Plan the project's structure, including modules, classes, and functions.
-
Implement your project using Python, adhering to best practices and design principles.
-
Test and refine your project to ensure it meets the desired outcomes.
Develop a Python Portfolio
Show steps
Creating a portfolio of Python projects will showcase your skills, provide a tangible representation of your learning, and aid in your professional development.
Show steps
-
Select a diverse range of projects that demonstrate your proficiency in various Python concepts.
-
Document your projects thoroughly, including descriptions, code snippets, and explanations.
-
Host your portfolio on a publicly accessible platform, such as GitHub or a personal website.
-
Continuously update your portfolio with new projects and refine existing ones.
Create a Course Summary
Show steps
By compiling a course summary, you'll reinforce your understanding of the course material and create a valuable resource for future reference.
Show steps
-
Review course notes, assignments, quizzes, and exams.
-
Summarize key concepts, definitions, and examples.
-
Organize the summary into logical sections.
-
Review and refine your summary regularly.
Review Python Basics
Show steps
By reviewing the fundamentals of Python syntax and programming concepts, you'll strengthen your understanding of the upcoming lessons.
Browse courses on
Python Syntax
Show steps
Show steps
Show steps
- Refer to online tutorials or documentation to recap Python syntax.
- Revisit basic programming concepts, such as variables, data types, and operators.
- Complete practice problems to test your understanding.
Explore Python Functions
Show steps
By exploring guided tutorials on Python functions, you'll gain a deeper understanding of how to define, call, and utilize functions to structure and modularize your code effectively.
Show steps
Show steps
Show steps
- Search for online tutorials or documentation that cover Python functions.
- Follow along with the tutorials, practicing the creation and implementation of functions.
- Experiment with different function parameters and return values.
- Apply your knowledge to real-world coding scenarios.
Collaborative Python Coding
Show steps
Engaging in collaborative Python coding sessions with peers will allow you to share knowledge, troubleshoot problems, and reinforce your understanding of the course material.
Show steps
Show steps
Show steps
- Connect with classmates or online communities to form study groups.
- Choose a specific topic or project to work on together.
- Regularly meet to discuss ideas, solve problems, and provide feedback.
- Utilize collaborative coding tools or platforms to work on projects together.
Three other activities
Expand to see all activities and additional details
Show all six activities
Design a Python Project
Show steps
Designing a Python project will provide you with hands-on experience in applying the concepts learned in the course, fostering a deeper understanding of Python programming.
Show steps
Show steps
Show steps
- Brainstorm project ideas that align with your interests and course objectives.
- Outline the project's goals, scope, and functionality.
- Plan the project's structure, including modules, classes, and functions.
- Implement your project using Python, adhering to best practices and design principles.
- Test and refine your project to ensure it meets the desired outcomes.
Develop a Python Portfolio
Show steps
Creating a portfolio of Python projects will showcase your skills, provide a tangible representation of your learning, and aid in your professional development.
Show steps
Show steps
Show steps
- Select a diverse range of projects that demonstrate your proficiency in various Python concepts.
- Document your projects thoroughly, including descriptions, code snippets, and explanations.
- Host your portfolio on a publicly accessible platform, such as GitHub or a personal website.
- Continuously update your portfolio with new projects and refine existing ones.
Create a Course Summary
Show steps
By compiling a course summary, you'll reinforce your understanding of the course material and create a valuable resource for future reference.
Show steps
Show steps
Show steps
- Review course notes, assignments, quizzes, and exams.
- Summarize key concepts, definitions, and examples.
- Organize the summary into logical sections.
- Review and refine your summary regularly.
Career center
Learners who complete Programming with Python Fluency will develop knowledge and skills
that may be useful to these careers:
Management Consultant
Management Consultant
Management Consultants use Python to analyze data and make recommendations to businesses. This course teaches Python fundamentals, which are essential for building a successful career as a Management Consultant.
Data Scientist
Data Scientist
Data Scientists use Python to develop machine learning models that can identify patterns in data. This course teaches Python fundamentals, which are essential for building a successful career as a Data Scientist.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers use Python to build and deploy machine learning models. This course teaches Python fundamentals, which are essential for building a successful career as a Machine Learning Engineer.
Business Analyst
Business Analyst
Business Analysts use Python to analyze data and identify business problems. This course teaches Python fundamentals, which are essential for building a successful career as a Business Analyst.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use Python to develop mathematical models for business problems. This course teaches Python fundamentals, which are essential for building a successful career as an Operations Research Analyst.
Statistician
Statistician
Statisticians use Python to analyze data and draw conclusions. This course teaches Python fundamentals, which are essential for building a successful career as a Statistician.
Software Engineer
Software Engineer
Software Engineers use Python to develop software applications. This course teaches Python fundamentals, which are essential for building a successful career as a Software Engineer.
Data Analyst
Data Analyst
Data Analysts provide data-driven insights to inform business decisions. This course teaches Python, a powerful programming language used for data analysis. By learning Python, you can build a foundation for a successful career as a Data Analyst.
Web Developer
Web Developer
Web Developers use Python to build websites and web applications. This course teaches Python fundamentals, which are essential for building a successful career as a Web Developer.
Financial Analyst
Financial Analyst
Financial Analysts use Python to analyze financial data and make investment recommendations. This course teaches Python fundamentals, which are essential for building a successful career as a Financial Analyst.
Data Engineer
Data Engineer
Data Engineers use Python to build and maintain data pipelines. This course teaches Python fundamentals, which are essential for building a successful career as a Data Engineer.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use Python to develop mathematical models for financial markets. This course teaches Python fundamentals, which are essential for building a successful career as a Quantitative Analyst.
Actuary
Actuary
Actuaries use Python to assess risk and develop insurance products. This course teaches Python fundamentals, which are essential for building a successful career as an Actuary.
Data Science Manager
Data Science Manager
Data Science Managers lead teams of data scientists and engineers. This course teaches Python fundamentals, which are essential for building a successful career as a Data Science Manager.
Machine Learning Manager
Machine Learning Manager
Machine Learning Managers lead teams of machine learning engineers. This course teaches Python fundamentals, which are essential for building a successful career as a Machine Learning Manager.
For more career information including salaries, visit:
OpenCourser.com/course/ndmlil/programming
Reading list
We've selected 15 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
Programming with Python Fluency.
Provides a comprehensive introduction to Python programming, covering essential concepts such as data types, variables, operators, and control flow. It features hands-on projects and exercises to reinforce learning, making it a valuable resource for beginners looking to build a strong foundation in Python.
This practical guide introduces Python programming through real-world projects and tasks, such as web scraping, data analysis, and automating repetitive tasks. It provides a hands-on approach to learning Python, making it suitable for beginners with little to no programming experience.
Save
This engaging and interactive book uses a visual and humorous approach to teach Python programming concepts. It features puzzles, exercises, and real-world examples to make learning enjoyable and memorable.
Save
This classic textbook provides a comprehensive introduction to computer science and programming using Python. It covers fundamental concepts such as problem-solving, algorithms, and data structures, making it a valuable resource for beginners looking to develop a deeper understanding of programming.
Save
This comprehensive textbook introduces Python programming in the context of computer science. It covers a wide range of topics, including data structures, algorithms, and object-oriented programming. It is suitable for beginners with little to no programming experience who want to gain a solid foundation in Python.
Save
This intermediate-level book delves into advanced Python features and techniques, including object-oriented programming, decorators, generators, and metaprogramming. It provides insights into Python's design and implementation, making it suitable for experienced programmers looking to enhance their Python skills.
Save
This practical cookbook provides a collection of recipes and solutions for common Python programming tasks. It covers a wide range of topics, from basic syntax to advanced techniques, making it a valuable reference for experienced Python programmers looking to solve specific problems.
Save
This concise guide offers practical advice and best practices for writing effective and maintainable Python code. It covers topics such as code readability, performance optimization, and exception handling, making it a valuable resource for experienced Python programmers looking to improve their coding skills.
Save
This comprehensive reference provides a concise and authoritative overview of the Python language and its standard library. It covers a wide range of topics, from basic syntax to advanced features, making it a valuable resource for experienced Python programmers looking for a quick and reliable reference.
This comprehensive reference guide to the Python Standard Library provides detailed documentation on all built-in modules and functions. It is an essential resource for experienced Python programmers looking for in-depth information about the standard library.
Save
This comprehensive textbook provides a thorough introduction to Python programming and computer science. It covers a wide range of topics, from basic syntax to advanced concepts, making it suitable for beginners looking for a solid foundation in Python and computer science.
This practical guide introduces Python for data analysis and data science. It covers topics such as data exploration, data cleaning, and data visualization, making it suitable for beginners looking to use Python for data-related tasks.
This comprehensive textbook provides a thorough introduction to machine learning using Python. It covers a wide range of topics, from supervised learning to unsupervised learning, making it suitable for students and programmers looking to develop their machine learning skills.
This textbook introduces natural language processing (NLP) using Python. It covers topics such as text preprocessing, feature extraction, and machine learning for NLP, making it suitable for students and programmers looking to develop their NLP skills.
This specialized textbook introduces Python for bioinformatics. It covers topics such as sequence analysis, gene expression analysis, and molecular evolution, making it suitable for students and researchers in bioinformatics.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/ndmlil/programming
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Effort
8 hours
Via
Udacity
Language
English
Good to know
Suitable for beginners, it can aid learners in establishing a basic foundation in Python
Practical in nature, it can help learners apply Python to create visual representations using a virtual 'turtle' robot
Covers essential Python concepts, including loops, compound statements, and functions
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