Find & compare on-demand or live online Python bootcamps. We’ve chosen 0 of the best Python bootcamps from the top training providers to help you find the perfect fit.
In this data science bootcamp, students will build programming skills and data analysis skills using Python. This course is open to beginners and is meant to get individuals up and running with Python programming and data science to generate insights from data. Topics covered include programming fundamentals, working with data frames, data analysis, data visualization, and statistical analysis. This course offers flexible scheduling options and a free retake for students to refresh the materials.
Learn the essential skills and tools to become a Python Developer. This beginner-friendly course teaches students Python for software development with Django and Django REST in addition to other developer tools such as Git and SQL. After completing this certificate, students will be able to apply for the following roles: Python Developer, Back End Developer, Software Engineer, and many more.
The Fullstack Academy Artificial Intelligence & Machine Learning bootcamp provides current and prospective data professionals with the in-demand skills to specialize in this lucrative, dynamic, and rapidly-growing field. Over 26 weeks part-time, students will learn practical and theoretical machine learning concepts using real-world tools—graduating with the working knowledge and experience needed to qualify for a range of data roles, including those concentrated in AI. Students will also receive professional career coaching support for up to a year following graduation to help build and maintain an ideal, specialized career path in the industry.
In the Python for Data Science Masterclass, students learn both foundational and advanced Python programming skills, including data types, control flow, and object-oriented programming. The curriculum covers data science libraries like NumPy and Pandas for data manipulation and Matplotlib and Seaborn for data visualization. The course also covers advanced techniques such as web scraping, database querying, and using APIs.
The Advanced Python for Data Science Bootcamp teaches students how to refine their Python programming skills by learning advanced functions, web scraping techniques, and working with JSON data and APIs. The lessons cover regression analysis, creating complex visualizations, and integrating SQL in Jupyter Notebooks. The course also dives into the use of libraries like Seaborn and Beautiful Soup for data visualization and web scraping, respectively.
Develop AI-powered web apps in this advanced Python course, where you'll use Flask and the OpenAI API to create dynamic sentiment analysis applications. Gain essential skills in web development, error handling, and deployment, taking your Python projects to a professional level with real-world AI integration.
This 1-week data analytics course provides a deep-dive into using Python for data analysis. Students will get comfortable with the basics of Python programming and start working with critical data analysis libraries like Numpy, Pandas, and Matplotlib to perform data analysis and create data visualizations. This 35 hour intensive is meant to quickly get beginners in Python up to speed on performing data analysis and visualization in Python.
This 1-week Python Immersive is geared towards beginners with no prior coding experience and meant to give students a fundamental understanding of Python to start coding on their own. Students will learn best practices for coding with Python, work on exercises and programs in Python, and conclude with 2 projects of their own.
The University of New Mexico Continuing Education AI & Machine Learning Bootcamp, powered by Fullstack Academy, offers a comprehensive 26-week part-time program designed to accommodate working professionals seeking to advance their skills in AI and machine learning. This active learning approach combines lectures, labs, and projects, allowing students to acquire hands-on experience and practical knowledge applicable both remotely and in New Mexico's growing tech industry.
The AI & Machine Learning Bootcamp at the University of San Diego, powered by Fullstack Academy, offers a dynamic 26-week part-time curriculum, welcoming students from various professional backgrounds into the world of artificial intelligence and machine learning. This program blends theoretical knowledge with practical application, using lectures, labs, and projects to equip students with the skills needed for existing roles or new careers in the data field.
The Online AI & Machine Learning Bootcamp at the University of North Florida, a 26-week part-time program powered by Fullstack Academy, offers students from diverse professional backgrounds the opportunity to master AI and machine learning skills. This comprehensive course combines lectures, labs, and projects, utilizing Fullstack Academy's active learning approach to provide practical, real-world tool application, preparing students for careers in the fast-growing data field.
This course provides an introduction to the use of Python programming language for data analysis. Python, through the use of list and string manipulation, control structures, and data analysis packages, can be used to manage and analyze large sets of data. In this course, you will learn how to use Scipy, Numpy, Pandas, Seaborn and matplotlib to analyze data and create visualizations. This course has 4 units, covering list manipulation, strings and simple I/O, control structures and data analysis packages. IPython notebook is also used to show how codes and change codes are used during class.
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Learning Python sets you up for meaningful work in two specific fields: development and data. Developers focus on building websites or software and use Python and its frameworks to build both the front and back end of websites. Data careers rely on Python to analyze data, make predictions and valuable insights, and build data systems.
Python is one of the core skills needed to secure one of these positions. See the career pages for more information on required skills, tips for landing a job, typical day-to-day work, and where to find job postings.
Indeed.com Avg. Salary
$81K / year
Glassdoor Avg. Salary
$81K / year
Web developers build webpages using coding languages such as HTML, CSS, and JavaScript. They program functionality and identify/troubleshoot errors in code. Web developers can work on front-end development (the part of the website you see in a web browser), or on back-end development (the logic and database functionality that runs on the web server). Others work as full-stack developers, providing end-to-end (front to back) expertise.
Indeed.com Avg. Salary
$105K / year
Glassdoor Avg. Salary
$117K / year
Software engineers use their extensive knowledge of user experience design, operating systems, and programming languages to develop software. They can create different types of software, from games to operating systems. After analyzing a client's needs, they design, develop, and test software to meet that need. Software engineers can be divided into two distinct career categories: application engineers and systems engineers.
Indeed.com Avg. Salary
$158K / year
Glassdoor Avg. Salary
$89K / year
A Back End Developer builds the server-side of a web application and integrates front end development components.
Indeed.com Avg. Salary
$133K / year
Glassdoor Avg. Salary
$97K / year
Python Developers typically choose to focus on back end web development, data science or analysis, scripting, or product development. They build the server side of websites, processes for data analysis, and create automation scripts.
Indeed.com Avg. Salary
$127K / year
Glassdoor Avg. Salary
$91K / year
Full Stack Developers build web applications for both the visible front end that users see and the back end that powers the applications.
Indeed.com Avg. Salary
$161K / year
Glassdoor Avg. Salary
$121K / year
Machine Learning Engineers create computer programs that enable machines to take actions without being specifically directed to perform those tasks. This job combines computer programming and data science to enable systems to learn and improve from experience automatically by using machine learning, a subset of artificial intelligence.
Indeed.com Avg. Salary
$129K / year
Glassdoor Avg. Salary
$105K / year
Data Engineers create the infrastructure for data and format data into a useful system which Data Scientists use to analyze large amounts of data. Data Engineers can specialize in pipelines, databases or platforms, warehouses or infrastructure, or be generalists.
Indeed.com Avg. Salary
$122K / year
Glassdoor Avg. Salary
$115K / year
Data scientists collect, organize, and analyze large sets of data, providing analysis that is key to decision making. Governments, non-profits, and businesses of all types rely on data for forecasting, risk management, and resource allocation. Data scientists discover and analyze trends in data, and report their findings to stakeholders. They will use algorithms and models to simplify and mine data sets to create data-driven recommendations. Data scientists are needed across a handful of industries, especially the ubiquity of data and the reliance on it for business decision-making.
Indeed.com Avg. Salary
$79K / year
Glassdoor Avg. Salary
$84K / year
Data analysts review large amounts of data to summarize, analyze, and visualize it and provide insights. Working from data from multiple, relevant sources, they create and maintain databases, and use statistical techniques to analyze the collected data. Data analysts must be able to communicate with others about what the data shows and to be able to provide realistic recommendations based on their analysis. Many industries such as healthcare, advertising, and retail rely on the work of data analysts to inform their business decisions and strategy.
Python has remained in the top most-used programming languages for the past several years, and for good reason. The language is powerful and flexible, driving data science, machine learning algorithms, and the back end of web applications. Python is also simple and easy to learn because its syntax mimics human language.
With a substantial collection of libraries, Python supports work in prototyping machine learning models, computation, data analysis, dimensional plotting and statistical modeling, and web scraping. As an open-source language, Python is powered and maintained by its large community of programmers, who also serve as a helpful resource for new learners. Python is an essential tool in any programmer’s toolkit and an excellent language for beginners to learn.
For students looking to leverage the knowledge of Python into a job, learning the language can lead to two main career paths: application development and data science. Students should have a good idea about in which area they want to use their Python skills when they plan their course trajectory, as developers and data professionals use different frameworks and libraries in their work. For instance, a Back End Web Developer will use the Django and Flask frameworks to produce websites quickly. On the other hand, a Machine Learning Engineer may use libraries including NumPy, Pandas, TensorFlow, and Scikit-learn to create neural networks.
Learning Python for web development and software engineering opens up many challenging and profitable careers. Lifelong learners can find opportunities for advancement by continuing to add more languages and skills to their resumes. Even on the low end, Web Developers earn a respectable average of $70,000 annually in the US, using languages like Python and HTML, CSS, and JavaScript, and Python to produce websites. Workers who are especially proficient in both front end and back end languages, including Python, earn over $100,000 annually as Full Stack Developers. Specializing in Python can unlock an average salary over $110,000 as a Python Developer. At the same time, extensive experience with Python and other major and niche programming languages helps Back End Developers and Software Engineers to bring in over $120,000 each year.
Python data skills also help students enter careers throughout the data lifecycle. Data Engineers design data pipelines, data warehouses, and other data infrastructures to supply data for later analysis and use. In the US, Data Engineers bring in substantial salaries, $125,000 on average. Data Scientists gather and process the data that Data Engineers deliver, earning an annual average over $130,000 as they perform complex analyses on and across datasets.
Data Analysts also use their communication skills to visualize data and generate reports for clients and stakeholders to use in decision-making processes. Because Data Analysts do not need to know as many libraries and algorithms as other data professionals, the threshold for entry into the data analysis job market is lower, as is the average annual income, which is around $70,000. However, Data Analysts have more room for growth into other jobs in the data lifecycle.
Machine Learning Engineers develop computer automations for data processing as well as self-improving programs. With their hybrid skills in data science and application development, Machine Learning Engineers earn upwards of $125,000 annually on average.
There are several differences between live online and on-demand classes to be aware of. On-demand classes deliver content and assessments via online modules and pre-recorded videos, which means that training is always available at the student’s own pace. Students with busy or irregular schedules can progress through the course as they have time, and students in time zones that aren’t supported by live training have more options to learn Python. Those with unreliable internet connections can also benefit from on-demand Python classes, especially text-based courses with significantly lower bandwidth.
For students with different learning needs, on-demand Python classes can provide the accessibility of self-paced learning, lecture videos that can be replayed, and a low-pressure learning environment. On-demand courses are also frequently priced lower than in-person and live online classes, making them a more-affordable, lower-commitment option to start learning Python.
Live online Python classes offer even more opportunities for students to learn the language. These classes combine the convenience of virtual training with the real-time interaction and hands-on guidance of an in-person course. These classes are understandably more expensive than on-demand learning, but they provide additional benefits including networking opportunities and career support.
Over the years, several major players have entered the field of on-demand Python education. LinkedIn Learning, Skillshare, and Udemy are three MOOC (Massive Open Online Course) platforms that allow educators to make their on-demand classes available to interested learners. On LinkedIn Learning and Skillshare, students can pay a subscription fee to access courses such as Python Essential Training, Python 3: A Beginner’s Guide to Python Programming, and 100 Days of Code: The Complete Python Pro Bootcamp for 2022, as well as other courses in the platform’s catalog. Students can buy individual on-demand courses from Udemy, allowing them to take classes such as Python for Finance: Investment Fundamentals & Data Analytics and 2022 Complete Python Bootcamp From Zero to Hero in Python. MOOC platforms host a wide variety of courses in Python, providing students with many opportunities to find the class that fits their learning style and training needs.
In addition to MOOC platforms, dedicated on-demand coding schools also offer Python training courses. These education providers offer students coherent catalogs of courses and clear learning paths as they progress through their Python training journey. Codecademy’s Learn Python 3 and SkillCrush’s Python for Web Apps and Data courses are suitable for students interested in data and development careers. DataCamp’s Introduction to Python helps students learn skills targeted for data analysis, while Simplilearn hosts a Python Certification Course for future web developers.
For those just starting to explore Python, Noble Desktop offers two free on-demand Python tutorials to help students decide if the language is right for them. Exchanging Excel for Python allows students to learn how Data Analysts use Python in their work, while Python Tutorial: Making a Twitter Bot in Python gives students a taste of developing applications with Python.
Noble Desktop runs several live online Python classes for students looking to get started with the language. Students seeking a development-oriented introductory class can take the Python Programming immersive to learn computer science fundamentals and object-oriented programming.
Beginners interested in data analytics can enroll in Noble’s Data Analytics Certificate. This program is excellent for those hoping for rapid upskilling in the language, including Pandas, NumPy, and MatPlotLib for data visualization. Python is also extensively covered throughout the Data Science Certificate program at Noble Desktop. This course includes training in SQL, machine learning, and Scikit-learn, as well as a final portfolio project and individual career mentoring sessions.
A career-accelerating option for students pursuing the developer path is the Python Developer Certificate program, which teaches students how to use Python, SQL, and Django to craft web applications. Students receive mentorship and career support as they work on their portfolio projects.
Students who wish to fill a gap in their Python knowledge or grow within their current career may prefer to study in a live online Python bootcamp. Though their title may sound intimidating, bootcamps are often less intense than a longer course. Typically, bootcamps are accelerated programs designed to quickly teach a more targeted skill. These types of programs aren’t as comprehensive as the certificates mentioned above, but they are ideal for professionals who need to learn additional skills for a promotion or to boost their resumes.
Noble Desktop offers a Python for Data Science Bootcamp. This program focuses on Python’s use in the booming data science field. Here, students learn how to manage different types of data and improve their workflow by reusing their code with object-oriented programming. Python libraries like Pandas and Numpy are covered as well. Those in the financial industry may benefit from attending Noble’s FinTech Bootcamp instead. This program includes all of the information covered in the data science bootcamp and additional topics relevant to finance, such as how to build and analyze financial models using various Python libraries.
Both of these bootcamps guarantee small class sizes, so students receive optimal support throughout the learning process. They also include hands-on projects that students can add to their portfolios once the course is finished. These projects can help them stand out when applying for a promotion or pivoting to a new career. Additionally, participants in either bootcamp are afforded a free retake within one year. This allows students to refresh themselves on more difficult concepts and gain additional practice, meaning they’ll complete additional assignments for their portfolios.
With the many different options available, many students may have trouble deciding which method to choose when learning Python. Each option– in-person, live online, and on-demand– has their own advantages and drawbacks, and it’s important to consider them before enrolling in a course.
On-demand learning is an understandably appealing option due to its low cost and flexibility. It can be ideal for folks who want to learn the basics before taking a more extensive approach. Although Python has a reputation for its easy-to-learn syntax, beginners encounter plenty of challenges. For instance, many new learners find it difficult to understand the purpose of Python’s unique libraries and frameworks. Access to a live instructor can help students navigate difficulties rather than forcing them to stumble around on their own. On-demand Python courses also have the potential to contain outdated information, which is not the case with live instruction.
Learning Python in a live online course is an excellent way to combine some of the advantages of on-demand learning with the benefits of in-person instruction. Learning online provides more accessible options for students living in rural areas or relying on public transportation. Although these courses meet at pre-determined times, they allow flexibility in situations involving illness or bad weather. Plus, why leave home if you’re only going to work on your computer anyways? An interactive online Python course also allows students to network with like-minded professionals and get feedback on their projects so they know they’re headed in the right direction.
Employers investing in upskilling their staff can turn to online corporate Python training for professional and consistent workforce education in the programming language. Noble Desktop allows enterprises and organizations to request tailored private live online classes delivered virtually to the client’s offices via a teleconferencing platform such as Zoom. Employers can also buy vouchers for Noble Desktop’s open-enrollment Python courses for greater flexibility in live online training for their workers.
Group discounts are available with the purchase of multiple vouchers, which can then be distributed to multiple employees for the same Python class or different classes at different Python training levels, or to one employee training in multiple levels of Python. Employers can contact Noble Desktop for details.
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