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Marc Scott
and
James Robinson
On this course, you’ll explore Python programming at an intermediate level.
You'll discover how to break down problems into smaller parts, and then design and apply algorithms to data. You’ll also explore list structures and their various uses.
Read more
On this course, you’ll explore Python programming at an intermediate level.
You'll discover how to break down problems into smaller parts, and then design and apply algorithms to data. You’ll also explore list structures and their various uses.
Read more
On this course, you’ll explore Python programming at an intermediate level.
You'll discover how to break down problems into smaller parts, and then design and apply algorithms to data. You’ll also explore list structures and their various uses.
Ultimately, what you learn will build upon your foundational Python skills - preparing you to progress onto more advanced programming.
What you'll learn
Over the following four weeks, you will:
- Produce your own functions to break down problems into more manageable parts
- Apply several common search and sort algorithms to data
- Compare the efficiency of algorithms
- Modify functions to take parameters and output return values
- Interpret algorithms expressed in plain English, in pseudocde and as flowcharts
Register for this course and see more details by visiting:
OpenCourser.com/course/wvr63a/programming
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What's inside
Learning objectives
- Produce your own functions to break down problems into more manageable parts
- Apply several common search and sort algorithms to data
- Compare the efficiency of algorithms
- Modify functions to take parameters and output return values
- Interpret algorithms expressed in plain english, in pseudocde and as flowcharts
- Produce your own functions to break down problems into more manageable parts
- Apply several common search and sort algorithms to data
- Compare the efficiency of algorithms
- Modify functions to take parameters and output return values
- Interpret algorithms expressed in plain english, in pseudocde and as flowcharts
Syllabus
You will cover:
Use functions with parameters and return values
Design and apply algorithms to data
Breaking down problems into smaller parts
Read more
Syllabus
You will cover:
Use functions with parameters and return values
Design and apply algorithms to data
Breaking down problems into smaller parts
Read more
Searching and sorting
Efficiency of algorithms
Understanding of list structures and their uses
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
For students already versed in programming fundamentals
Teaches methods for efficiently managing and sorting data
Introduces list structures and their applications
Applies algorithms to real-world data examples
Requires prior programming knowledge
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Save Programming 102: Think Like a Computer Scientist 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 102: Think Like a Computer Scientist with these
activities:
Review basic Python syntax
Show steps
Refreshing your knowledge of Python syntax will make following along with new concepts easier.
Browse courses on
Python Syntax
Show steps
-
Go through an online Python tutorial
-
Complete a few practice exercises
Read 'Python Programming: An Introduction to Computer Science'
Show steps
This book provides a comprehensive overview of Python programming fundamentals and will help you build a strong foundation.
View
Python Programming: An Introduction to Computer...
on Amazon
Show steps
-
Go through the book thoroughly
-
Complete the exercises at the end of each chapter
Follow a Python tutorial series
Show steps
Following a structured tutorial series can help you learn Python systematically and efficiently.
Show steps
-
Find a reputable Python tutorial series
-
Follow the tutorials step-by-step
-
Complete the exercises and assignments
Five other activities
Expand to see all activities and additional details
Show all eight activities
Join a Python study group
Show steps
Discussing Python concepts with peers can help you understand and retain information better.
Show steps
-
Find a Python study group in your area or online
-
Attend study group meetings regularly
-
Participate in discussions and ask questions
Attend a Python Meetup
Show steps
Connecting with other Python developers can help you learn new techniques and stay up-to-date on the latest trends.
Show steps
-
Find a Python Meetup in your area
-
Attend the Meetup and introduce yourself to other attendees
-
Participate in discussions and ask questions
Solve coding challenges
Show steps
Applying your knowledge to solve coding problems will help you master the algorithms covered in the course.
Show steps
-
Find a website or platform that offers coding challenges
-
Start with easier challenges and gradually work your way up
-
Don't be afraid to ask for help if you get stuck
Write a blog post about a Python algorithm
Show steps
Explaining an algorithm in your own words will help you understand it deeply.
Show steps
-
Choose an algorithm that you're interested in
-
Research the algorithm and understand how it works
-
Write a blog post explaining the algorithm in detail
-
Share your blog post with others
Build a Python project
Show steps
Working on a real-world Python project will give you hands-on experience and help you apply your skills.
Show steps
-
Decide on a project idea
-
Plan and design your project
-
Implement your project
-
Test and debug your project
-
Deploy your project
Review basic Python syntax
Show steps
Refreshing your knowledge of Python syntax will make following along with new concepts easier.
Browse courses on
Python Syntax
Show steps
Show steps
Show steps
- Go through an online Python tutorial
- Complete a few practice exercises
Read 'Python Programming: An Introduction to Computer Science'
Show steps
This book provides a comprehensive overview of Python programming fundamentals and will help you build a strong foundation.
View
Python Programming: An Introduction to Computer...
on Amazon
Show steps
Show steps
Show steps
- Go through the book thoroughly
- Complete the exercises at the end of each chapter
Follow a Python tutorial series
Show steps
Following a structured tutorial series can help you learn Python systematically and efficiently.
Show steps
Show steps
Show steps
- Find a reputable Python tutorial series
- Follow the tutorials step-by-step
- Complete the exercises and assignments
Five other activities
Expand to see all activities and additional details
Show all eight activities
Join a Python study group
Show steps
Discussing Python concepts with peers can help you understand and retain information better.
Show steps
Show steps
Show steps
- Find a Python study group in your area or online
- Attend study group meetings regularly
- Participate in discussions and ask questions
Attend a Python Meetup
Show steps
Connecting with other Python developers can help you learn new techniques and stay up-to-date on the latest trends.
Show steps
Show steps
Show steps
- Find a Python Meetup in your area
- Attend the Meetup and introduce yourself to other attendees
- Participate in discussions and ask questions
Solve coding challenges
Show steps
Applying your knowledge to solve coding problems will help you master the algorithms covered in the course.
Show steps
Show steps
Show steps
- Find a website or platform that offers coding challenges
- Start with easier challenges and gradually work your way up
- Don't be afraid to ask for help if you get stuck
Write a blog post about a Python algorithm
Show steps
Explaining an algorithm in your own words will help you understand it deeply.
Show steps
Show steps
Show steps
- Choose an algorithm that you're interested in
- Research the algorithm and understand how it works
- Write a blog post explaining the algorithm in detail
- Share your blog post with others
Build a Python project
Show steps
Working on a real-world Python project will give you hands-on experience and help you apply your skills.
Show steps
Show steps
Show steps
- Decide on a project idea
- Plan and design your project
- Implement your project
- Test and debug your project
- Deploy your project
Career center
Learners who complete Programming 102: Think Like a Computer Scientist will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
Data analysts use programming skills to extract insights from data, identifying trends and patterns that can help businesses make better decisions. Programming 102: Think Like a Computer Scientist can help data analysts build a strong foundation in Python programming, which is a valuable skill in this field. The course covers topics such as data structures, algorithms, and problem-solving, all of which are essential for data analysts.
Software Engineer
Software Engineer
Software engineers use programming languages to design, develop, and maintain software applications. Programming 102: Think Like a Computer Scientist can help software engineers enhance their Python programming skills and learn how to solve complex programming problems. The course covers topics such as algorithm design, data structures, and software design patterns, which are all important for software engineers.
Data Scientist
Data Scientist
Data scientists use programming skills to build statistical models and machine learning algorithms to analyze data and solve business problems. Programming 102: Think Like a Computer Scientist can help data scientists strengthen their Python programming skills and learn how to apply programming concepts to data analysis. The course covers topics such as data structures, algorithms, and machine learning, which are all valuable for data scientists.
Computer Programmer
Computer Programmer
Computer programmers use programming languages to develop software applications. Programming 102: Think Like a Computer Scientist can help computer programmers improve their Python programming skills and learn how to solve programming problems more efficiently. The course covers topics such as algorithm design, data structures, and software design principles, which are all important for computer programmers.
Web Developer
Web Developer
Web developers use programming languages to design and develop websites. Programming 102: Think Like a Computer Scientist can help web developers build a strong foundation in Python programming, which is a valuable skill in this field. The course covers topics such as data structures, algorithms, and web development frameworks, which are all important for web developers.
Machine Learning Engineer
Machine Learning Engineer
Machine learning engineers use programming skills to build and deploy machine learning models. Programming 102: Think Like a Computer Scientist can help machine learning engineers strengthen their Python programming skills and learn how to apply programming concepts to machine learning. The course covers topics such as data structures, algorithms, and machine learning techniques, which are all valuable for machine learning engineers.
Data Engineer
Data Engineer
Data engineers use programming skills to build and maintain data pipelines and data warehouses. Programming 102: Think Like a Computer Scientist can help data engineers develop a strong foundation in Python programming, which is a valuable skill in this field. The course covers topics such as data structures, algorithms, and data management, which are all important for data engineers.
Software Developer
Software Developer
Software developers use programming languages to design, develop, and maintain software applications. Programming 102: Think Like a Computer Scientist can help software developers improve their programming skills and learn how to solve complex programming problems. The course covers topics such as algorithm design, data structures, and software design patterns, which are all essential for software developers.
Quantitative Analyst
Quantitative Analyst
Quantitative analysts use programming skills to build financial models and analyze financial data. Programming 102: Think Like a Computer Scientist can help quantitative analysts build a strong foundation in Python programming, which is a valuable skill in this field. The course covers topics such as data structures, algorithms, and statistical modeling, which are all important for quantitative analysts.
Business Analyst
Business Analyst
Business analysts use programming skills to analyze business data and identify opportunities for improvement. Programming 102: Think Like a Computer Scientist can help business analysts build a strong foundation in Python programming, which is a valuable skill in this field. The course covers topics such as data structures, algorithms, and data visualization, which are all important for business analysts.
Information Security Analyst
Information Security Analyst
Information security analysts use programming skills to protect computer systems and networks from cyber threats. Programming 102: Think Like a Computer Scientist can help information security analysts develop a strong foundation in Python programming, which is a valuable skill in this field. The course covers topics such as data structures, algorithms, and network security, which are all important for information security analysts.
Operations Research Analyst
Operations Research Analyst
Operations research analysts use programming skills to solve complex problems in business and industry. Programming 102: Think Like a Computer Scientist can help operations research analysts build a strong foundation in Python programming, which is a valuable skill in this field. The course covers topics such as data structures, algorithms, and optimization techniques, which are all important for operations research analysts.
Financial Analyst
Financial Analyst
Financial analysts use programming skills to analyze financial data and make investment recommendations. Programming 102: Think Like a Computer Scientist can help financial analysts build a strong foundation in Python programming, which is a valuable skill in this field. The course covers topics such as data structures, algorithms, and financial modeling, which are all important for financial analysts.
Actuary
Actuary
Actuaries use programming skills to analyze risk and uncertainty in financial and insurance applications. Programming 102: Think Like a Computer Scientist can help actuaries develop a strong foundation in Python programming, which is a valuable skill in this field. The course covers topics such as data structures, algorithms, and statistical modeling, which are all important for actuaries.
Statistician
Statistician
Statisticians use programming skills to analyze data and make inferences. Programming 102: Think Like a Computer Scientist can help statisticians build a strong foundation in Python programming, which is a valuable skill in this field. The course covers topics such as data structures, algorithms, and statistical modeling, which are all important for statisticians.
For more career information including salaries, visit:
OpenCourser.com/course/wvr63a/programming
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
Programming 102: Think Like a Computer Scientist.
Save
This introductory Python book is commonly used as a textbook at academic institutions. It provides a solid foundation in Python programming, including functions, algorithms, and data structures.
This German-language textbook provides a comprehensive overview of algorithms, including searching, sorting, and graph algorithms. It valuable reference for students who want to read about algorithms in their native language.
This classic algorithms textbook provides a comprehensive overview of essential algorithms, including searching, sorting, and graph algorithms. It valuable reference for understanding the algorithms covered in the course.
Save
This open-source Python textbook covers a wide range of topics, including data structures, algorithms, and object-oriented programming. It great resource for additional reading and deepening your understanding of Python concepts.
This advanced textbook provides a comprehensive treatment of data structures and algorithms, with a focus on Python implementations. It valuable reference for students who want to delve deeper into these topics.
Save
Provides a collection of Python algorithms for various tasks, such as searching, sorting, and graph traversal. It useful reference for students who want to implement algorithms in Python.
Save
This introductory Python textbook covers essential computer science concepts, including algorithms, data structures, and object-oriented programming. It provides a good foundation for understanding the topics covered in the course.
Provides a comprehensive overview of data structures and algorithm analysis, using Java as the programming language. It valuable reference for students who want to learn about these topics in a different programming language.
Provides a concise overview of essential algorithms, including searching, sorting, and graph algorithms. It good resource for students who want to quickly review these topics.
This classic algorithms textbook provides a comprehensive overview of essential algorithms, including searching, sorting, and graph algorithms. It valuable reference for students who want to delve deeper into these topics.
Save
Provides a simplified introduction to essential algorithms, including searching, sorting, and graph algorithms. It good resource for students who want to learn about these topics in an accessible way.
Provides a comprehensive guide to algorithm design, including techniques and strategies for solving a wide range of computational problems. It valuable reference for students who want to learn how to design efficient algorithms.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/wvr63a/programming
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Effort
2 to 4 hours per week for 4 weeks
Level
Introductory
Via
edX
Institution
Raspberry Pi Foundation
Instructors
Marc Scott
James Robinson
Language
English
Transcript
English
Good to know
For students already versed in programming fundamentals
Teaches methods for efficiently managing and sorting data
Introduces list structures and their applications
Applies algorithms to real-world data examples
Requires prior programming knowledge
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