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Programming 102

Think Like a Computer Scientist

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.

Ultimately, what you learn will build upon your foundational Python skills - preparing you to progress onto more advanced programming.

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

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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

Searching and sorting

Efficiency of algorithms

Understanding of list structures and their uses

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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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

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Refreshing your knowledge of Python syntax will make following along with new concepts easier.

Browse courses on Python Syntax

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Go through an online Python tutorial
Complete a few practice exercises

Read 'Python Programming: An Introduction to Computer Science'

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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

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Go through the book thoroughly
Complete the exercises at the end of each chapter

Follow a Python tutorial series

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Following a structured tutorial series can help you learn Python systematically and efficiently.

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Find a reputable Python tutorial series
Follow the tutorials step-by-step
Complete the exercises and assignments

Five other activities

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Join a Python study group

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Discussing Python concepts with peers can help you understand and retain information better.

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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

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Connecting with other Python developers can help you learn new techniques and stay up-to-date on the latest trends.

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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

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Applying your knowledge to solve coding problems will help you master the algorithms covered in the course.

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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

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Explaining an algorithm in your own words will help you understand it deeply.

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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

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Working on a real-world Python project will give you hands-on experience and help you apply your skills.

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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 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.

See salaries and explore the career path for Data Analyst

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.

See salaries and explore the career path for Software Engineer

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.

See salaries and explore the career path for Data Scientist

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.

See salaries and explore the career path for Computer Programmer

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.

See salaries and explore the career path for Web Developer

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.

See salaries and explore the career path for Machine Learning 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.

See salaries and explore the career path for Data Engineer

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.

See salaries and explore the career path for Software Developer

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.

See salaries and explore the career path for Quantitative 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.

See salaries and explore the career path for Business 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.

See salaries and explore the career path for Information Security 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.

See salaries and explore the career path for Operations Research 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.

See salaries and explore the career path for Financial Analyst

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.

See salaries and explore the career path for Actuary

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.

See salaries and explore the career path for Statistician

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.

Head First Python

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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.

Programming 102

Think Like a Computer Scientist

What you'll learn

What's inside

Learning objectives

Syllabus

Good to know

Save this course

Activities

Career center

Reading list

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