It is an accessible, beginner-friendly language that is easy to learn and versatile enough to utilize in almost any project. Python is used in software engineering, web development, game design, and data science projects. Advanced data science projects, in particular, including machine learning and artificial intelligence applications, rely heavily on Python and its libraries, so if this cutting-edge technology interests you, learning Python is a necessary skill to acquire. No matter what kind of work you are hoping to do in the field of computer science, it is likely that Python will be a productive programming language to learn.
1) NextGen Bootcamp: Python Data Science & Machine Learning
NextGen Bootcamp’s Python Data Science & Machine Learning Summer program is an ideal course for students looking for a robust and comprehensive Python training program. In this course, students will learn how to program with Python, one of the most versatile programming languages in the world and among the most essential languages in data science. This course is a good place to learn the basics of computer programming since Python is one of the more straightforward programming languages for new coders. In the first half of the course, students will learn how to write, read, and compile basic Python code, after which they will begin learning how to work with large datasets and write conditional statements and queries essential to working with datasets.
In the latter half of the course, students will learn how to use Pandas, Matplotlib, and scikit-learn. These are dedicated data science Python frameworks allowing programmers to use Python code to organize, query, interpret, and visualize their data. Students will work on hands-on projects designed to guide them through building and interpreting complex datasets using Python. They will also learn how to create clean and evocative data visualizations like graphs and charts to communicate information about their data. The course concludes by covering the fundamentals of using Python to program machine learning algorithms and the functions of artificial intelligence. The course aims to provide students with a solid understanding of all of the major topics in data science and prepare them to continue their Python and machine learning training as part of a college computer science curriculum.
Students who have taken this course regularly praise the depth and breadth of the content offered. One student wrote that “we covered something new every day, which made me feel that I was exploring a lot about Python, ” while another noted that the “class really helped to improve my programming skills and knowledge! It covers a good span of topics ranging from vanilla Python programming to machine learning.”
2) NextGen Bootcamp Computer Science Summer Certificate Program
Students looking for a more comprehensive computer science summer education that still emphasizes Python can enroll in NextGen Bootcamp’s Computer Science Summer Certificate Program. This program combines NextGen’s Python Data Science and Machine Learning program and its SummerJava Programming course, aiming to provide students with a comprehensive introduction to computer science. Python and Java are two of the most accessible programming languages for new programmers. They are also the two languages most commonly taught in high school AP computer science programs and introductory college computer science courses. This course is a beginner-friendly program for students to learn basic computer science concepts. Students enrolled in this class will learn how to read code and write large programs, and these skills are transferable to almost any computer science-related field.
Students will start by learning how to write and read Java code. Building on these skills, students will learn the differences between procedural and object-oriented programming and how to write programs using both. Students will gain critical foundational skills that will benefit them as they learn more complex programming languages. Not only is Java useful in theory, but it is also an essential language for software engineering projects, so learning it also has practical applications. Once students are comfortable with Java, they will learn how to write code with Python. These lessons will teach them to apply that programming knowledge to data science tasks, like writing complex queries or using Python libraries to visualize data. Students who complete this program will gain a robust knowledge of Java and Python programming and be prepared to continue their training at a collegiate or professional level.
Students who have taken this course speak highly of the accessible and beginner-friendly instruction. One student said the course “has laid out an easy-to-follow path for me while also allowing me to learn so much in just 15 days.” Another student called it “a great class for coding beginners who want to learn the basics of Python.” This course is perfect for anyone hoping to learn foundational programming skills or anyone interested in learning computer science but unsure where to start.
3) Digital Media Academy: Data Literacy in a Global Society
Some students may not be interested in diving headfirst into a Python-heavy training course when they are starting their data science training. Digital Media Academy’s Data Literacy in a Global Society course is an ideal place for these students to learn the theoretical and practical concerns surrounding data science and the most common applications for Python programming skills. This course focuses on the logic and processes associated with data science and machine learning, and students will receive training in thinking like a data science programmer. After learning about the basics of computational logic, the course will focus on data literacy, including lessons on how data is commonly utilized in real-world contexts and how new data tracking and analyzing processes impact major aspects of our everyday lives.
This is an introductory course for students before enrolling in a more advanced data science course, particularly for students who need help determining what kind of data science work interests them the most. In this course, students will learn how data impacts the global economy and how it is used to monitor and understand everything from global politics to our television and film viewing habits. This course introduces the practical, social, and ethical questions surrounding big data and data analytics, emphasizing the practical concerns raised by big data collection projects. This education will serve as a vital foundation for the kinds of work students are tasked to do with data if they pursue their education further.
4) Digital Media Academy: Applications Programming & Web Development with Python & HTML and CSS
Python isn’t only utilized in data science projects, so students interested in learning how the language can be used to design web applications should consider enrolling in Digital Media Academy’s Applications Programming & Web Development with Python & HTML and CSS. In this course, students will get hands-on instruction and practice programming simple applications using Python. Then, they will learn how to write working webpages coded in HTML and CSS that run those applications. Some possible projects include building working calculators, card shufflers, interactive calendars, and measurement converters, all of which will be integrated into web development projects. This course will give students practical training in writing and debugging code, and students will learn the typical workflow process of working on a computer science project, including the step-by-step process of planning, charting, and developing a working Python application.
This course is part of Digital Media Academy’s Tech Accelerator program, which aims to prepare high school students for university or professional-level computer programming work. These courses allow students to benefit from real-world tech partnerships to help prepare them to achieve their long-term career goals. This program encompasses multiple courses, and students who continue with the program will curate a development portfolio, receive one-on-one mentorship and training sessions with tech and creative professionals, and they will be able to enroll in Industry Masterclasses in which they can begin working on more complex development projects. This program is designed for students who want to start their professional development as early as possible and know they want to pursue a career in a Python-related development field.
5) Practical Programming: Introduction to Python Programming
Some students may want to start their Python education slowly, and these students should consider a course like Practical Programming’s Introduction to Python Programming. In this course, students will get a general overview of Python, one of the most versatile programming languages new students can learn, and its most frequently used functions. Students who learn Python will set themselves up for future success in software engineering, web development, game design, or data science since all these fields regularly utilize Python or its major libraries. This course also serves as a broad introduction to computer science. It will help students better understand the programming process since they will still learn all the basics of computer coding, like reading and writing code.
This course, in particular, is an accelerated Python training program designed for students 18 and over, making it a good fit for students entering their senior year or graduating and looking for a bit more training before they start their freshman year. Over two class meetings, students will learn the basics of writing Python code, and they will learn more broadly applicable programming skills, like how to use code editing applications and efficiency tools like Git. This course aims to provide students with a thorough understanding of Python's syntax, grammar, and vocabulary. Upon finishing the program, students will have a foundational understanding of Python that they can use for more complex projects or additional training. Courses like this are an ideal introduction to computer programming for students without a deep background in the field or who want to learn Python at a slower pace.
Students who have attended this course report that this is a “great class to get started with Python, ” and felt they were given a solid foundation in the material. The instructors in particular are praised as being knowledgeable and flexible, often willing to pause a lesson to ensure all students understood what was being taught. Some reviewers did point out that students were most successful when they spent time outside of class taking advantage of the provided self-study materials, so factoring in additional time is something to consider before enrolling in this program. The class is reportedly beneficial for students who want to learn Python for personal enjoyment or to build professional skills.
6) Practical Programming: Python Machine Learning Immersive
Students looking for a more advanced course may want to look at options like Practical Programming’s Python Machine Learning Immersive course. This is an ideal introduction to the Python skills students will need to utilize machine learning algorithms. Students enrolled in this course will learn how to use their existing Python knowledge to write logical and linear regression models that allow machine learning algorithms to function. Students will also learn the statistical concepts that underpin a machine learning algorithm's ability to create accurate models and forecast information based on the datasets that they are trained on. This course will also cover important theoretical concepts such as bias and variance so that students who work with machine learning algorithms can create more accurate and useful datasets on which their algorithms can be trained. This is a vital process since poor or inaccurate data will render even the most complex and detailed machine learning algorithm useless. The most well-crafted algorithm in the world won’t be of much use if the data that is being trained on is inaccurate or the people responding to the algorithm's output aren’t trained to read data.
Students as young as 13 can start practicing AI and machine learning development skills from their homes in this accelerated, remote learning program. This course aims to teach students how to use machine learning algorithms in practical, real-world scenarios, and the hands-on instruction provides them with the tools to start training their own algorithms. The instruction that students receive in this course is geared toward business and data analytic processes, but it applies to almost any data science-related task. Students will need a background knowledge of Python (the equivalent of an introductory level course) to enroll in this program. In addition, students will need a background in computational mathematics because the course will touch on subjects of advanced computational statistics.
7) UConn Pre-College: Data Science
Another option for high school students looking to learn Python over the summer is to enroll in a pre-college course. Many colleges and universities offer summer programs for high students, allowing them to earn college credit and learn in a collegiate setting. A great many of these programs emphasize STEM training, including The University of Connecticut, which offers a pre-college Data Science program for students interested in learning Python and R programming. This course is centered on the statistical analysis of games. Lessons use simple and complex games as a means of demonstrating data tracking and analysis, and students will learn how to use R to program and analyze their own sample games. Students working in this class will get hands-on experience in computer programming and data science, making this course an ideal entry point into the world of data analytics, regardless of a student’s background in programming. Students will learn the practical aspects of statistical analysis, domain knowledge, and computer science, which are essential aspects of building foundational programming skills.
This program is taught by members of the UConn mathematics faculty and aims to provide students with a college-level statistical analysis experience. Students enrolled in the course will receive hands-on, practical training in math and computer science, and they will learn these skills in a college classroom environment. Once students become comfortable with their data science and statistical analysis knowledge, they will begin working on lab projects that allow them to apply this knowledge outside the classroom. Students will learn how to use Python libraries to visualize their data, giving them the tools they need to communicate their findings to a generalist audience. This course doesn’t provide UConn college credit, but it will demonstrate your commitment to your STEM education to college admission boards.
8) Syracuse University: Data Visualization and Analysis
High school students entering their sophomore, junior, or senior years or students who graduated high school in 2025 are all eligible to apply for Syracuse University’s on-campus, pre-college Data Visualization and Analysis program. In this course, students will learn how to transform raw data into actionable insights and rhetorically effective visualizations, utilizing Python libraries to streamline this process. In this hands-on program, students will learn how data is collected and how data science experts analyze the quality and accuracy of this data. Students will also learn how to use data analytics tools to help them read and interpret massive datasets, starting with instructions on using Microsoft Excel. In addition, students will work hands-on with software applications like Tableau to learn how to transform data into persuasive charts, maps, and graphs that can be used to communicate findings to non-specialized audiences.
Students' time in this class is divided between workshop lessons and hands-on lab time in which students collaborate on group data science projects. These hands-on lessons are designed to give students practical experience working with the kinds of datasets they expect to encounter in a college class or professional setting. This course is built for students looking to start honing practical data analytics skills while learning how to use industry-standard tools like Tableau. This summer session is taught by Syracuse University professors, lasts one week, and is on campus so that students can access the university’s technology labs. Students who complete this course may be able to receive transferable college credit, and all students who complete the course will receive a university certificate of completion.
9) iDTech: Python Coding: Arcade Games and AI
Some students may want to enroll in a course that takes a more project-oriented approach to teaching Python than many introductory coding classes take to teaching computer programming basics. These students may want to consider a class like iDTech’s Python Coding: Arcade Games and AI course. Students will learn the basics of programming in Python by developing arcade-style games that utilize the language, designing, testing, and iterating on the game as they learn more complex Python skills. At the start of the class, students will design simple logic games. Then, they will move on to more advanced object-oriented programming projects, including adding graphical elements to their arcade games. Students will get hands-on lessons in the practical uses of Python in software engineering projects, which makes this an ideal class for students interested in game design, app development, or software engineering.
Since Python is such an accessible first programming language for new learners, students without prior programming experience can enroll in this course to start learning the language. Students will start learning how to use Python to write code for interactive, logic-driven games and to add responsive user interface elements to their designs almost right away, and students will quickly be able to see and interact with the fruits of their labor. Python is a versatile language, so students enrolled in the course will learn a wide range of uses for the programming language. For example, students will learn how to program interactive movement into a game and how to program simple artificial intelligence scripts for oppositional elements of their games, all using Python. After they have completed the final project for the course, students will have completed a working arcade game that they can include as part of their application materials for jobs, internships, and college coding programs.
10) Pacific University: Sports Analytics Camp
One of the reasons that Python is such a popular programming language is that data analytics is becoming an in-demand professional skill as more and more industries are developing tailored data analytics techniques to gain a competitive edge in the marketplace. While many Python courses focus on the basics of the language or the use of data analytics in business and finance, some courses focus on more narrow applications such as Pacific University’s Pre-college Sports Analytics Camp. In this program, students will apply Python skills, data analytics, and advanced quantitative methodologies to professional sports, business, and competitive landscapes. Students will work with experienced data analytics professors and professionals and will have the opportunity to meet and work with experienced industry experts. This course is a good fit for students who want to learn about the practical applications of data science and Python programming to specific fields and industries since learning these skills can be an excellent way to find a career you are passionate about.
Students enrolled in this course will learn the practical applications of Python and data science in the field of sports analysis. These range from lessons in using advanced analytics and metrics to predict player and team performance to lessons on how this quantitative research can inform long-term decision-making. Other lessons will cover the various less visible ways that data analytics and Python impact the sports industry, including seminars focusing on collegiate athletics and scouting, fantasy and esports, and fan engagement strategies. Class time will also be dedicated to learning about the career paths that exist in sports analytics, offering students the opportunity to learn what career paths they can follow in the industry and what additional training they will need to achieve their goals.
Why Enroll in a Python Summer Program?
Given its popularity and versatility, learning Python is a great introduction to the world of computer science. The language is used in everything from data science and analytics to software development and game design. Since it is an accessible, beginner-friendly language, it is a good starting point for students without prior programming experience. However, it is still a deep enough language that learning Python will pay off in the long run, regardless of what path your computer science career takes you on. Once you have learned Python, you can start learning major Python programming libraries and start working on projects involving things like machine learning and artificial intelligence programs.
Python is also a very in-demand professional skill, particularly for specialists working in data science and machine learning. Data science jobs are some of the fastest-growing jobs in the country, with the Bureau of Labor Statistics anticipating that they will grow by as much as 36% year over year during the next decade. Data scientists also command high salaries due to their specialized skill set and the critical role they play in extracting actionable insights from data. Job security and high earning potential aside, data science is an excellent career path for students who value continuous knowledge. With new technologies, techniques, and tools emerging regularly, data science provides endless opportunities for professionals to learn and grow throughout their careers. They can also apply their skills to socially meaningful work such as improving healthcare outcomes and addressing societal challenges.
As more and more industries begin utilizing data analytics and other Python functions to garner competitive advantages, the demand for Python experts will only continue to grow. Additionally, Python’s use in software and game development ensures that it isn’t just data science experts who will be able to find work. Python is also frequently utilized in back-end web development. Specifically, two of its frameworks, Django and Flask, are popular choices for web developers because of their security and scalability. In fact, Python is used in the server-side development of globally popular websites like Netflix, Reddit, and Pinterest. Similar to data science, web development jobs are also expected to rise at a faster-than-average rate over the next ten years. If you are considering your long-term future and are interested in computer science, learning Python can be the first step to maximizing your career earning potential.
Regardless of their overall career goals, learning Python can help develop additional valuable professional skills across a wide range of roles and industries. For instance, using Python encourages students to think creatively as they design innovative solutions and applications. Learning Python is also an excellent way to learn critical thinking skills and new approaches to complex problems. Students learning the language will need to think like programmers and consider the affordances and limitations of Python when they are approaching a data science or digital development project. Developing projects with Python also typically requires collaboration with peers, allowing students to enhance their ability to work in a team and develop strong communication skills since they will often need to explain technical concepts effectively.
For beginner programmers, learning Python can feel like learning a new language since they will need to master Python’s syntax and grammar to work with it. Luckily, once they’re comfortable programming with Python, additional coding languages will be much easier to learn. Python's simplicity and versatility make it an ideal starting point for beginners because it provides a solid foundation of fundamental programming concepts like variables and data types. Once this knowledge is in place, advancing to more complex languages like Java, C++, or JavaScript becomes more manageable since many of the concepts learned in Python are transferable. Learning additional languages can lead to a broader range of job opportunities and a higher earning potential.
On a more practical level, taking a summer Python program can be a good way to jump-start your future computer science training, earn college credit, or receive professional certificates and accreditations. Many summer programs offer support with developing a resume or a portfolio that displays your projects in a professional and visually appealing way. They are also great ways to help students hone their strengths and interests. Since Python is used for developing video games, building websites, analyzing data, and creating applications, students can take a summer class to see what piques their interest, potentially saving valuable time and money when deciding what subjects to focus on in their college education.
How to Choose a Python Summer Program
After reviewing the Python courses that are offered over the summer, the next step is to consider which one will best meet your needs. For many students, a program's price and available financial aid is the primary concern. While learning Python programming skills can definitely lead to commanding a higher salary, spending a thousand dollars or more on a summer class can be a challenge for lots of students and their families. If finances are tight, it may be best to research programs that offer scholarships, financial aid, or other monetary benefits. For example, some courses offer free retakes of their entire program, allowing students to take advantage of additional practice opportunities and expert mentoring for free.
Students should also consider the environments in which they learn best prior to enrolling in a summer program. Some students may find that they learn best from in-person courses because they are the most similar to a traditional classroom. In contrast, others prefer the additional flexibility and convenience you often find in an online program. There is no wrong way to learn Python, but reflecting on your preferred learning style can help you make a more informed decision about the program you wish to attend. For instance, if you know you get anxious around new people, you may feel more at ease in an online program from the comfort of your home. While it may take a bit of extra time initially, thinking about the factors most important to your education will go a long way toward choosing the summer Python course that is most likely to help you accomplish your goals.