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Python is one of the most popular and in-demand programming languages in the world — largely because of how readable and versatile it is. If you’re interested in learning Python, this free, introductory course will demonstrate how learning to code in Python could benefit your career. No previous programming experience is required.
Read more
Python is one of the most popular and in-demand programming languages in the world — largely because of how readable and versatile it is. If you’re interested in learning Python, this free, introductory course will demonstrate how learning to code in Python could benefit your career. No previous programming experience is required.
Read more
Python is one of the most popular and in-demand programming languages in the world — largely because of how readable and versatile it is. If you’re interested in learning Python, this free, introductory course will demonstrate how learning to code in Python could benefit your career. No previous programming experience is required.
From analyzing large datasets to building web applications, Python can be used for a variety of projects including:
- Writing scripts for automating tasks
-Web development
-Collecting data from websites (also known as “web scraping”)
-Scientific and numeric computing
-Data analysis
-Data visualization
-Machine learning
Python is also a useful skill applicable to roles across a wide range of industries, including:
-Energy
-Finance
-Healthcare
-Marketing
-IT
-Retail
This course is an introduction to our Boot Camps, which combine data analysis and machine learning to prepare learners for careers such as data analysts, financial analysts, data scientists, and more.
This Try It is offered in support of the Data Analytics Boot Camp, Coding Boot Camp, and FinTech Boot Camp with Arizona State University. If you enroll in this Try It, your learner data will not be shared with Arizona State University unless you enroll in the Data Analytics Boot Camp, Coding Boot Camp, or FinTech Boot Camp.
Register for this course and see more details by visiting:
OpenCourser.com/course/9a77yw/try
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What's inside
Learning objectives
- -what python is and where it’s used.
- -functions, the bits of code that tell python what to do.
- -how to create and name variables.
- -how to build conditional logic to automate dual-alternative decision-making.
- -how to use python for advanced decision making with nested if/else statements.
- -how python interacts with a console.
- -how to code simple programs and use conditional statements to automate decision-making.
- -what python is and where it’s used.
- -functions, the bits of code that tell python what to do.
- -how to create and name variables.
- -how to build conditional logic to automate dual-alternative decision-making.
- -how to use python for advanced decision making with nested if/else statements.
- -how python interacts with a console.
- -how to code simple programs and use conditional statements to automate decision-making.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Explores the breadth of Python applications, from automating tasks to machine learning
Demystifies Python syntax and structures, making coding accessible to beginners
Introduces programming fundamentals like variables, functions, and conditionals
Provides a solid foundation for individuals seeking careers in data analytics, financial analysis, and data science
Designed to complement Arizona State University's Data Analytics and FinTech Boot Camps
Save this course
Save Try It: Intro to Python 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 Try It: Intro to Python with these
activities:
Python coding exercises
Show steps
Brush up on the basics of Python syntax and coding to prepare for this course.
Browse courses on
Python Basics
Show steps
-
Review Python variables, data types, and operators.
-
Practice writing simple Python programs.
Data Analytics with Python
Show steps
Reinforce your understanding of Python's capabilities for data analysis.
Show steps
-
Follow tutorials on data cleaning, data manipulation, and data visualization with Python.
-
Complete exercises and practice using Python libraries for data analysis, such as Pandas and NumPy.
Show all two activities
Python coding exercises
Show steps
Brush up on the basics of Python syntax and coding to prepare for this course.
Browse courses on
Python Basics
Show steps
Show steps
Show steps
- Review Python variables, data types, and operators.
- Practice writing simple Python programs.
Data Analytics with Python
Show steps
Reinforce your understanding of Python's capabilities for data analysis.
Show steps
Show steps
Show steps
- Follow tutorials on data cleaning, data manipulation, and data visualization with Python.
- Complete exercises and practice using Python libraries for data analysis, such as Pandas and NumPy.
Show all two activities
Career center
Learners who complete Try It: Intro to Python will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
A Data Analyst collects, analyzes, interprets and presents data. They use their findings to identify trends and patterns that can be used to make better decisions. Python is a valuable tool for Data Analysts, as it allows them to automate data analysis tasks and build complex data visualizations. This course will help you build a strong foundation in Python, which will be essential for success in your career as a Data Analyst.
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer develops and deploys machine learning models. They use programming languages to create code that trains and evaluates machine learning models. Python is one of the most popular programming languages for Machine Learning Engineers, as it is versatile and can be used to work with a variety of machine learning algorithms and data types. This course will help you build a strong foundation in Python, which will be essential for success in your career as a Machine Learning Engineer.
Data Scientist
Data Scientist
A Data Scientist uses scientific methods to extract knowledge from data. They develop and use statistical models, machine learning algorithms, and data visualization techniques to identify patterns and trends in data. Python is one of the most popular programming languages for Data Scientists, as it is versatile and allows them to work with a variety of data types and formats. This course will help you build a strong foundation in Python, which will be essential for success in your career as a Data Scientist.
Data Engineer
Data Engineer
A Data Engineer builds and maintains the infrastructure that is used to store and process data. They use programming languages to create code that automates data processing tasks and ensures that data is reliable and accessible. Python is one of the most popular programming languages for Data Engineers, as it is versatile and can be used to work with a variety of data types and formats. This course will help you build a strong foundation in Python, which will be essential for success in your career as a Data Engineer.
Financial Analyst
Financial Analyst
A Financial Analyst uses financial data to make investment recommendations and decisions. They analyze financial statements, market trends, and economic data to identify potential investment opportunities. Python is becoming increasingly popular among Financial Analysts, as it can be used to automate data analysis tasks, build financial models, and perform risk analysis. This course will help you build a strong foundation in Python, which will be essential for success in your career as a Financial Analyst.
Data Visualization Engineer
Data Visualization Engineer
A Data Visualization Engineer designs and develops data visualizations. They use programming languages to create code that converts data into visual representations, such as charts, graphs, and maps. Python is one of the most popular programming languages for Data Visualization Engineers, as it is versatile and can be used to create a wide variety of data visualizations. This course will help you build a strong foundation in Python, which will be essential for success in your career as a Data Visualization Engineer.
Quantitative Analyst
Quantitative Analyst
A Quantitative Analyst uses mathematical and statistical models to analyze financial data. They use their findings to make investment recommendations and decisions. Python is becoming increasingly popular among Quantitative Analysts, as it can be used to automate data analysis tasks, build financial models, and perform risk analysis. This course will help you build a strong foundation in Python, which will be essential for success in your career as a Quantitative Analyst.
Financial Risk Manager
Financial Risk Manager
A Financial Risk Manager uses mathematical and statistical models to assess and manage financial risk. They use their findings to make recommendations on how to mitigate risk and protect the financial health of organizations. Python is becoming increasingly popular among Financial Risk Managers, as it can be used to automate data analysis tasks, build financial models, and perform risk analysis. This course will help you build a strong foundation in Python, which will be essential for success in your career as a Financial Risk Manager.
Actuary
Actuary
An Actuary uses mathematical and statistical models to assess risk and uncertainty. They use their findings to make recommendations on insurance rates, pension plans, and other financial products. Python is becoming increasingly popular among Actuaries, as it can be used to automate data analysis tasks, build financial models, and perform risk analysis. This course will help you build a strong foundation in Python, which will be essential for success in your career as an Actuary.
Operations Research Analyst
Operations Research Analyst
An Operations Research Analyst uses mathematical and statistical models to solve complex business problems. They use their findings to make recommendations on how to improve business processes and systems. Python is becoming increasingly popular among Operations Research Analysts, as it can be used to automate data analysis tasks, build optimization models, and create data visualizations. This course will help you build a strong foundation in Python, which will be essential for success in your career as an Operations Research Analyst.
Statistician
Statistician
A Statistician uses statistical methods to collect, analyze, interpret, and present data. They use their findings to make informed decisions about a variety of topics, such as public health, climate change, and economic policy. Python is becoming increasingly popular among Statisticians, as it can be used to automate data analysis tasks, build statistical models, and create data visualizations. This course will help you build a strong foundation in Python, which will be essential for success in your career as a Statistician.
Software Engineer
Software Engineer
A Software Engineer designs, develops, and maintains software systems. They use programming languages to create code that meets the needs of users. Python is one of the most popular programming languages for Software Engineers, as it is versatile and can be used to develop a wide variety of software applications. This course will help you build a strong foundation in Python, which will be essential for success in your career as a Software Engineer.
Market Researcher
Market Researcher
A Market Researcher conducts research to understand consumer behavior and trends. They use their findings to make recommendations on how to improve marketing campaigns and products. Python is becoming increasingly popular among Market Researchers, as it can be used to automate data analysis tasks, build data visualizations, and create reports. This course will help you build a strong foundation in Python, which will be essential for success in your career as a Market Researcher.
Business Analyst
Business Analyst
A Business Analyst uses data analysis techniques to identify and solve business problems. They use their findings to make recommendations on how to improve business processes and systems. Python is becoming increasingly popular among Business Analysts, as it can be used to automate data analysis tasks, build data visualizations, and create reports. This course will help you build a strong foundation in Python, which will be essential for success in your career as a Business Analyst.
Web Developer
Web Developer
A Web Developer designs and develops websites. They use programming languages to create code that controls the appearance and functionality of websites. Python is one of the most popular programming languages for Web Developers, as it is versatile and can be used to develop a wide variety of websites. This course will help you build a strong foundation in Python, which will be essential for success in your career as a Web Developer.
For more career information including salaries, visit:
OpenCourser.com/course/9a77yw/try
Reading list
We've selected 14 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
Try It: Intro to Python.
Save
Serves as a comprehensive reference for Python programming, covering all aspects of the language from syntax to standard library modules. It valuable resource for learners who need a quick and reliable source of information on specific Python topics.
Save
Provides a unique perspective on learning Python by emphasizing the thought processes and problem-solving techniques used by computer scientists. It valuable resource for learners who want to develop a deeper understanding of the underlying principles of programming.
Save
Offers a more comprehensive and rigorous introduction to Python, covering a wide range of computer science concepts and algorithms. It is an excellent choice for learners who seek a strong foundation in the fundamentals of programming.
Builds upon the course's introduction to Python by providing a comprehensive overview of the language's core concepts and features. It is an excellent resource for learners who seek a deeper understanding of Python's syntax, data structures, and object-oriented programming.
Provides a comprehensive overview of machine learning techniques using Python libraries such as Scikit-Learn, Keras, and TensorFlow. It valuable resource for learners who want to gain practical experience in developing and deploying machine learning models.
Provides a practical and project-based approach to learning Python. It covers a wide range of topics, from basic data structures and algorithms to more advanced concepts such as web development and data analysis. It valuable resource for learners who want to gain hands-on experience in building real-world Python applications.
Complements the course's focus on practical applications of Python by offering a hands-on approach to automating everyday tasks. It is particularly useful for learners who are interested in developing scripts and programs to streamline their workflow.
Focuses on the use of Python in data analysis and data manipulation. It provides a comprehensive overview of the Pandas library, which is essential for working with tabular data in Python. It valuable resource for learners who want to develop their skills in data analysis and visualization.
Delves into the practical applications of Python in data science, covering topics such as data wrangling, visualization, and machine learning. It valuable resource for learners who are interested in pursuing a career in data analysis or data science.
Save
Provides a visual and interactive approach to learning Python, making it particularly suitable for learners who prefer a less traditional textbook format. It great resource for supplementing the course's materials with engaging and memorable content.
Save
Offers a concise and practical guide to writing more effective Python code, covering topics such as code readability, performance optimization, and error handling. It valuable resource for learners who want to improve the quality of their Python programs.
Save
Takes a more advanced approach to Python programming, focusing on best practices, code optimization, and design patterns. It valuable resource for learners who want to refine their Python skills and write more efficient and maintainable code.
Provides a collection of practical recipes and solutions for common programming tasks in Python. It serves as a valuable reference for learners who need to quickly find answers to specific coding challenges.
Save
Presents a collection of lesser-known and advanced Python features and techniques, providing learners with a deeper understanding of the language's capabilities. It valuable resource for learners who want to expand their Python knowledge and explore more efficient and elegant coding practices.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/9a77yw/try
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Effort
1 to 2 hours per week for 1 week
Level
Introductory
Via
edX
Institution
Arizona State University
Language
English
Transcript
English
Good to know
Explores the breadth of Python applications, from automating tasks to machine learning
Demystifies Python syntax and structures, making coding accessible to beginners
Introduces programming fundamentals like variables, functions, and conditionals
Provides a solid foundation for individuals seeking careers in data analytics, financial analysis, and data science
Designed to complement Arizona State University's Data Analytics and FinTech Boot Camps
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