Top 3 Options for Learning Python in a Bootcamp (to Stand Out in the Job Market)

To be competitive in today’s tech job market, you need top-notch skills. Learning how to code with Python through a bootcamp can be an effective way to get up to speed, find your dream job, and start getting paid for doing something you love.

Python is arguably one of the most popular programming languages among today’s top developers. In a 2020 Stack Overflow survey, nearly half of all responding developers said they use Python and also voted Python among their most-loved languages. Python is considered one of the easiest languages to learn, as the syntax is comparatively simple and uses English words. These features make Python an excellent option for industry newcomers, aspiring upskillers, and professionals looking to switch careers entirely. A Python bootcamp can help to compress that learning curve, saving time and money otherwise spent on a computer science degree.

Specialization is vital in today’s job market. Instead of studying computer science theory, multiple languages, and their corresponding technical skills in a college program, bootcamp learners can focus tightly on their chosen discipline. In doing so, they can develop proficiencies more quickly and pursue careers in coding, development, fintech, and a host of other tech industries.

Introduction to Python

Python is used just about anywhere modern technology is employed. Coders and developers use it to develop websites, produce video games, build mobile applications, interact with databases, power AI, and so much more. That makes Python an elemental language across multiple industries. But what is Python?

According to its developers, Python is “an interpreted, object-oriented, high-level programming language with dynamic semantics.” Guido Van Rossum developed Python in the late 1980s as an upgrade to the ABC programming language, deriving its name from the British comedy troupe Monty Python. Since then, Python has become widely used in many industries and, because of its versatility, is ideal for small- and large-scale projects. Python is viewed as incredibly popular among developers for nearly any job, making it a highly marketable and sought-after skill.

Python ranks as the “most wanted” coding language among developers, according to Stack Overflow’s 2020 Developer Survey, for a variety of reasons. It is simple, dynamic, and requires no code-compiling; making testing and debugging very fast.

Python’s syntax is generally simple and straightforward to read, making it equally easy to understand and debug. Python’s flexible programming language supports packages, modules, and classes, making it convenient to repurpose. Python also uses high-level data types and is accompanied by an extensive library that interfaces with operating systems, engineering functions, internet protocols, and general programming. Python is available in source or binary form and is free to download for all the major platforms (e.g., Linux, Unix, macOS, Windows).

Industries That Use Python

As a general-purpose language, Python delivers a practical reach across a variety of industries. Professionals who work in web development, fintech, scientific computing, and artificial intelligence are among those who write in Python. Major tech companies such as Google and YouTube rely on Python for a solid, secure infrastructure. Financial analysts can upskill by learning Python to work with data and databases.

Python is powerful enough to be used to create an entire OS itself. The Python standard library includes all the tools you need to create a fully functional desktop application with a graphical user interface (GUI). In fact, apps like BitTorrent and Dropbox are written in Python. The fintech industry uses Python generously to run complex calculations and deftly handle analytics, risk management, and data regulation.

Python is also widely used in coding mobile apps because it works great on iOS and Android. For example, some popular social media platforms, like Instagram, are written in Python. What’s more, with much of the future rooted in AI and machine learning, Python has robust, built-in resources and libraries (such as Scikit-Learn and TensorFlow) to use for those types of projects. The on-board Pandas and NumPy libraries also make Python ideal for data science and analytics projects. Have you heard of Carla, the autonomous-driving research simulator? It comes with a Python applied programming interface (API).

What Is a “Python Bootcamp”?

Since Python is such a desirable skill benefiting countless industries, dozens of educational institutions now offer bootcamps for newcomers starting fresh, and for established developers looking to upskill. A Python bootcamp is an intensive but flexible course that trains learners in the language quickly. Many of these courses focus primarily on a specific Python programming industry or skill set.

Though Python is incredibly useful and in-demand, finding a bootcamp dedicated solely to it is actually quite difficult. To prepare learners for a variety of roles, many bootcamps teach full tech skill sets instead of one specialized skill. For this reason, you’ll need to consider your long-term professional goals — namely, the role you hope to obtain in the future — to better inform your bootcamp course selection and increase your chances of finding your ideal position.

What Are the 3 Main Options for Learning Python in a Bootcamp?

When choosing a Python bootcamp, you should consider your desired career path. For example, if you plan to code financial apps, then your focus likely would be on the fintech industry. If you love working with data, you might want to focus on data analytics. Specializing your skills in a specific industry can also increase your marketability.

Columbia Engineering Boot Camps offer three course options that provide learners with the chance to gain Python skills, as well as associated, in-demand skills for the data analytics, coding, and fintech fields.

Data Analytics Bootcamps

Columbia Engineering Data Analytics Boot Camp is designed to prepare learners for a variety of roles in data science. This bootcamp covers a broad range of relevant tools and technologies, including statistical modeling, databases, and web visualization. Python is a part of this bootcamp’s core. Its second module, Python Data Analytics, focuses on the fundamentals of Python programming: working with APIs; data analytics tools such as NumPy, Pandas, and Matplotlib; and key libraries for data research, such as Beautiful Soup.

Though it’s a core component of the data analytics bootcamp, the Python module is accompanied by a variety of other modern tools and technologies used by data professionals. The course covers a broad range of tools that are important to data analytics. Learners gain advanced skills in Microsoft Excel (it’s far more than a spreadsheet) and dive into statistical forecasting. They also learn how to work with database tools such as SQL, MySQL, and NoSQL.

Learners also develop skills to present their data visually through programming languages such as HTML/CSS and JavaScript. They study advanced topics such as Tableau (a business intelligence software), Hadoop (a framework for data processing), and machine learning as well.

Columbia Engineering Data Analytics Boot Camp teaches more than technology. Learners test their ability to analyze and solve complex data problems, which are core skills in data analytics and in high demand across all industries and sectors.

Why Learn Python as Part of a Data Analytics Bootcamp?

Many of today’s tech and science employers are looking for the most well-rounded candidates possible. Python has become an increasingly important skill for those starting their journey to becoming a data analyst. In fact, not only does this skill set showcase your value to employers, it provides context to your skill set which increases marketability.

For this specific job market, learning Python and data analytics together can set you apart from the competition, make you a valuable asset to employers, and prepare you to confidently pursue roles such as these:

Coding Bootcamps

Coding bootcamps can be ideal for those just entering the field. They cater to a variety of experience levels, from beginners to those who have more familiarity with coding, and can flexibly fit into work schedules. Bootcamps are intensive and often move quickly — usually lasting 12-24 weeks — and offer curricula rooted in practical, hands-on instruction that typically simulate real-world coding scenarios. This allows learners to gain crucial coding skills in a timely, thorough manner.

Columbia Engineering Coding Boot Camp, for example, provides the foundation to enter full stack web development. The curriculum covers the front end essentials such as HTML, CSS, and JavaScript; back end technologies (Express.js, React.js. Node.js); and the ability to connect both ends together. Learners master these tools through real-world projects, interactive instruction, and personalized support.

Coding bootcamps offer a real-life understanding of how to build websites and how to create, edit, and use databases. Learners also practice execution of server-side development, use browser-based technologies, deploy command-line functions, as well as test, debug, and correct code.

Why Learn Python as Part of a Coding Bootcamp?

While Python is a highly desirable skill in many tech industries, it is especially applicable for roles in web development and coding. As the Stack Overflow developer survey underscored, developers use and want to learn Python. Furthermore, learning Python along with a core set of coding skills can help differentiate learners when applying for promising, potentially lucrative industry positions. Many such positions require programming skills along with other computer science disciplines. Python is among them.

In the Columbia Engineering Coding Boot Camp, Python is part of a continuation phase that also includes Java, C#, and using Amazon Web Services (AWS). In this phase, which is offered at no cost, learners can access 10 hours of project-based course content, which is available for one year after the bootcamp.

These continuation courses provide learners with an opportunity to boost their employability by demonstrating proficiency in additional programming tools and technologies, including Python. Learners also will have tangible projects to showcase in their portfolios, which are vital to entering the tech market.

Coding bootcamps can provide a valuable career gateway for tech newcomers, job upskillers, or professionals seeking a transition. Some of the options include web developer (front end, back end, and full stack), software developer, computer programmer, product manager, software engineer, and technical business analyst. Demand for positions such as these is expected to increase, as the U.S. Bureau of Labor Statistics (BLS) projects computer and IT career opportunities to grow by 11 percent through 2029.

FinTech Bootcamps

Technology has changed how we save money, how the financial industry lends and invests it, and how financial professionals work. Analysts today need technical skills to conduct accurate analyses, deliver timely forecasts, and work with blockchain technologies. Fintech bootcamps address these important skills and more.

Fintech bootcamps prepare learners for careers in the ever-evolving world of fintech. Curricula cover a range of skills needed to enter careers in the financial services, banking, investing, and blockchain.

In a fintech bootcamp, learners gain the cross-section of technical and analytical skills important to these jobs. Columbia Engineering FinTech Boot Camp begins with an introduction to the fundamentals of finance, including analysis and modeling, before moving to its technical modules. These cover working with databases and financial libraries, using machine learning applications in finance, as well as blockchain and cryptocurrency. Unfamiliar terms such as algorithmic trading, random forests, and K-nearest neighbors will be part of your toolkit by the course’s end.

Why Learn Python as Part of a FinTech Bootcamp?

Python is becoming an indispensable tool in fintech. According to Finextra Research, Python has become a major language of banking and financial service institutions, in part because it is the “machine learning language of choice” in the industry. That’s why Python has a substantial place in fintech bootcamps.

For example, the second module of Columbia Engineering FinTech Boot Camp focuses on Python. The curriculum consists of using Python, and its APIs, to conduct financial analysis and build applications using real-time data. It also covers the various tools (Pandas, NumPy, SciPy, and more) used with Python to work with data.

Learning Python as part of a bootcamp can be beneficial for those seeking jobs in fintech — and those jobs are multiplying. A 2020 global fintech report from PwC found that 80 percent of tech, media, and telecommunications companies, and 75 percent of those in financial services, are creating fintech jobs.

What kinds of opportunities are possible? Those who complete bootcamps will be qualified for a range of positions, including financial and risk analyst, research analyst, fintech product manager, blockchain developer, and more.

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