Best Python Classes Atlanta, GA: Find Courses & Onsite Training

Learn More About Atlanta Python Courses

In Greek mythology, Python was the name of a ferocious serpent who dwelled at the omphalos (that’s still the word for navel in Modern Greek) of the Earth. Apollo slew Python at Pitho, a name the god changed to Delphi as part of a rebranding strategy for the local oracle. The officiating priestess, who lapsed into a prophetic trance by inhaling either ethane fumes coming through a crack in the floor or burning oleander leaves, bore the title of Pythia. The root of Python, Pitho, and Pythia alike is the verb puthein, to rot, allegedly because of the stench of the decomposing giant snake. The word has since lost its connotation of decomposition (the Modern Greek word for that is sepo, cf. English sepsis), and, in Modern Greek, python only means the large snake native to the tropical and subtropical Eastern hemisphere that constricts its prey and then swallows it whole.

Guido van Rossum had none of that in mind when he created a computer language that would go on to become the most popular of the present moment. Van Rossum was born in Haarlem, the Netherlands in 1956, and took his time earning his degree in mathematics from the University of Amsterdam in 1982, having been more interested in the mainframe computer in the basement than pure mathematics. He subsequently obtained a master’s degree in mathematics and computer science, and took up a position with the Amsterdam Centrum Wiskunde & Informatica (CWI), the Center for Mathematics and Computer Science. There, he was assigned to a team that was creating a new programming language called ABC. The goal of ABC was to be an easy-to-learn alternative to the basic language of the day, which just so happened to be named BASIC. ABC was interpreted, high-level, simple, compact, and interactive.

It was also a dismal failure.

Over one of his Christmas holidays at CWI, for want of anything better to do, Van Rossum designed a new programming language that took into account some of the concepts that underlay the ABC project. The new language made its debut in 1989, and, while Van Rossum assumed full responsibility for his creation, he had, in fact, been working with input from people in the burgeoning world of the internet. In fact, Van Rossum ascribes the success of his new language to this cooperation with the world at large, as opposed to the failure of ABC, which was cooked up in a vacuum.

Van Rossum named his new language Python. He chose the name not because of snakes, nor even because of the Delphic Oracle’s priestess. Rather, the language was named, in a flash of irreverence, after Monty Python’s Flying Circus, a (many would argue the) British sketch comedy television show from the 1970s. There are traces of Monty Python-type humor in Python’s documentation, including the use of the words spam and eggs in place of the customary foo and bar as metasyntactic variables (that’s a fancy term for placeholders.) “Spam and Eggs” is one of the best known of all Monty Python routines. It pushes the bounds of zany in English language comedy, and even incorporates a chorus of singing Vikings. Don’t, however, look for programming in Python to be as much fun as watching the routine.

Although not more fun than a barrel of monkeys, Python must still have something, as it holds the number one spot on the TIOBE Index, a survey of the popularity of the various programming languages before the public. Using as its barometer the number of hits each language obtains on a group of the 25 best-known search engines led by Google, Wikipedia, and Amazon, the TIOBE Index is calculated monthly, and, in April 2024, as in April 2023, Python held the top position on the list. Looking at the evolution of the TIOBE Index for the 30 years since Python has existed, the language comes off as a late-blooming upstart. (TIOBE stands for The Importance of Being Earnest, more for the surface meaning of the title of Wilde’s play than the fact that the play is actually about two people who may or may not be named Ernest.) In 2019, Python was number 4 on the list, in 2009, it was sixth, and, in 1994, it was far out of the top ten, at number 29. Those same statistics have historically assigned the top positions to C, C++, and Java. Thus, in the past five years, Python has ousted what were, for decades, the top three programming languages. Moreover, the Python phenomenon seems only to be growing: its share of the pie increased nearly 2% from March 2023 to March 2024; over that same twelvemonth, C and Java both slid over 4%.

Note that the TIOBE Index doesn’t rate the best computer languages, nor even the ones that are the most used (as a barometer such as lines of code written might.) It just tabulates languages’ relative popularity in the broader cultural space. There is thus a great deal of buzz about Python at present, which prompts the question of why.

Python’s advantages are easier to explain than the operation of the language itself. Its first and perhaps most attractive feature is that it is uncommonly easy to read. Commands are largely in English (other programming languages speak either in tongues or in punctuation marks), and the syntax is streamlined and easy to follow. The syntax also makes extensive use of indentations to indicate where blocks of commands begin and end.

In addition to being easy to read, Python is relatively easy to learn. Indeed, it’s literally child’s play in books like Python for Kids and Coding Games in Python. Having the language be easy to grasp was one of Van Rossum’s prime directives in creating Python, and, while some quarters have called it easy to learn but hard to master, few languages will have you up and writing code faster than Python.

Python has a lively community of users, which is an important resource for programmers on tight schedules. If you have a question, there are a lot of online resources you can consult. Some of those are even human. The language also has a vast network of libraries of ready-to-wear code that you can take and plug into the program you’re writing to take care of basic (and not-so-basic) tasks. The libraries greatly facilitate programming in Python, and correspond to many of the different proposes to which the language can be turned: NumPy and SciPy are used for scientific computation, pandas is used for data analysis, Matplotlib is for plotting, NLTK works for natural language processing, and Scikit-learn is designed for machine learning, something at which Python is very adept.

Another of the advantages of Python is that it’s open-source. Software created with the language is done so under the aegis of the Python Software Foundation, which, until 2018, operated under the aegis of Van Rossum, its Benevolent Dictator for Life. Van Rossum resigned from the post, citing health reasons and exhaustion resulting from the relentless squabbling over certain proposed changes to the language, and did not name a successor. The Foundation, now run by committee, is a not-for-profit organization that makes the language and its source code available free to all comers. Open source means more than that, however: any software written in Python must make its source code available to the public, other programs may be derived from existing ones, and these derived programs must also make their source code available. Like much of the philosophy dating back to the early days of computer science, the open-source concept is distinctly libertarian.

Python comes with its own aesthetic philosophy, too. “The Zen of Python,” penned by developer Tim Peeters, is a series of 20 (actually 19) aphorisms that embody Van Rossum’s philosophy of how to use his language. The first of these axioms, “beautiful is better than ugly,” betrays a concern few computer languages have: that the code possess some sort of beauty. Python, with all its indents, was designed to look attractive on the screen. Another of the principles is “readability counts.” Although it’s often violated in practice, another good illustration of the language’s sought-after simplicity is that “there should be one—and preferably only one—obvious way to do it.” (The following dictum, however, wryly states that this obvious way may only be obvious at first to the Dutch.)

The usual definition of Python is that it’s a high-level, general-purpose language that is interpreted, object-oriented, and, a bit more metaphorically, comes with its batteries included. High-level means that the language’s syntax resembles human language. General purpose means what it usually does: Python can be used for just about anything, from machine learning and artificial intelligence to gluing together segments of programs that have been written in other languages. As for interpreted, the term exists in contradistinction to compiled languages: interpreted languages get sent to the processor one command at a time, rather than needing to be put first through a compiling-inator that readies the whole program for the processor. Contrary to how that might sound, interpreted languages take longer to go through the machine than compiled ones, although any losses in terms of seconds or even minutes when it comes to running the program are greatly offset by the months and even years that are saved by developing in a language as streamlined as Python. Object-oriented means that the language groups concepts together as objects, which are discrete clumps of data and code that, among other things, make it easier to find flies in the computational ointment. Finally, batteries included, coined after the batteries-not-included Christmas morning heartbreak of yore, refers to the extensive libraries available that enable developers to use Python without having to start at square one. That, in turn, goes back to the ease-of-use concept that underlies the language, which itself is summed up by the third of the “Zen of Python” aphorisms: “Simple is better than complex.”

What Can You Do with Python Training?

As Python is a general-purpose language, there really isn’t much that you can’t do with it. The way things stand and are expected to stand for some years to come, you could theoretically make an entire development career using only Python. That’s perhaps an extreme case, especially as Python is often used to cobble together chunks of code in other languages.

One very popular use of Python is scientific computation, especially in tandem with the NumPy and SciPy libraries that can handle such complicated mathematical functions as arrays and imaginary numbers. The language is thus extremely practical for data science: not only can Python handle massive crunching of numbers (and crunching of massive numbers), but the simplicity of Python’s syntax makes the code accessible to data analysts and scientists who lack a strong programming background.

Python is also employed in the development of web applications. Thanks to libraries such as Django, Flask, and Pyramid, the language can be adapted to create such things as ecommerce (Django includes built-in capabilities for online catalogs and customer checkout), social media platforms, and content management systems (CMS, including DjangoCMS, Mezzanine and Cobra.) Reddit, Uber, Netflix and Facebook are all examples of web applications that employ Python.

Another, and very à la page, use for Python is the field of machine learning and artificial intelligence. Among the language’s strengths in this area are its abilities in natural language processing and its ability to automate repetitive tasks. The algorithm that governs your YouTube recommendations is Python’s machine-learning abilities at work. It’s also the thing behind ChatGPT. Google is hugely fond of the language, and trusts it to hold together the mind-numbing super-secret (way more secret than the In ‘n’ Out Burger sauce that is rumored to be coming to Georgia ere long) algorithm that tabulates its engine’s search results. The nitty-gritty of the search algorithm is still written in C++, however, which is why it can be secret despite Python’s open-source policy. The language’s scalability (its ability to handle larger and larger amounts of data) makes it extremely useful for this type of work, which you can find yourself doing without too much fear of obsolescence, at least until the bots start to program each other.

What Will I Learn in a Python Class?

Studying Python will teach you the basics that you will need to know no matter what you intend to do with the language. After that, you’ll find yourself studying one or more of the language’s most-used libraries and frameworks. Here, what you want to do with Python will factor into the equation: if you’re studying to be a web developer, you’ll learn Django, while, if you want to pursue data science, you’ll probably find yourself working with NumPy, pandas, and a lot of math. There are libraries for AI and machine learning as well, including TensorFlow, and you’ll focus on those if your goal is to develop artificial intelligence applications. Finally, and no matter what path you choose, you’ll find that some of Python’s Zen will rub off on you.

Python

Obviously, the first thing you’re going to learn in a Python class is the language itself. You always have to start at the beginning, which with Python means learning about variables (basically storage containers for data values) and operators. Among the latter, * means multiplication, - can denote a negative number or mean subtraction, == means equal, and the logical operators and, or, and not are written out in English rather than symbols. There’s also the amusingly named walrus operator, :=, which is used to assign values such as true or false in expressions. (Note that the kerfuffle over allowing the walrus operator was the crisis that ended with Guido van Rossum stepping down from his position of Benevolent Dictator for Life.) You’ll also learn Boolean, strings, lists, loops, dictionaries, and functions. The meanings of these arcane terms will become apparent as you study the language. You’ll be amazed at how quickly you’ll know enough Python to be able to set up a digital game of Rochambeau or create a random password generator.

Django

With the basics of the language in hand, you can proceed to learn how to use Python for more compelling pursuits than just giving you someone with whom to play rock/paper/scissors. One of the most frequent follow-ups to basic Python is the Django framework, which greatly aids developers trying to create web applications. In particular, Django is designed to help with the server sides of web applications, and provides developers with a highly developed open-source framework that allows them to bypass having to create their applications from the ground up. Django can set up forms and user identification, and even has a password hashing system module available. If you want to use Python and make a career in web development, Django will rapidly become one of your best friends.

Data Science

Another direction in which your Python education can lead is the world of data science. That field requires the processing of sometimes enormous quantities of data, followed by the Data Analyst’s interpretation of past performance or the Data Scientist’s prognostications for an organization’s future performance. Python enters into this picture by virtue of its computational capabilities, which are enhanced by the existence of libraries such as NumPy (it helps to create large arrays and matrices and then perform calculations with them) and pandas (a tool for data analysis and manipulation.) One of Python’s selling points for data science is that the intelligibility of the language to Data Scientists who aren’t coders makes it possible for the latter to look at and, if need be, get their hands dirty with the code they’re using. Another Python strong point for data science is its vaunted scalability, which, in this case, means that it can handle the kinds of really Big Data companies use today to power their crystal balls.

Machine Learning and AI

A further application for Python is the currently much-discussed field of machine learning. An offshoot of advanced statistics, machine learning is a means of letting the computer do the gruntwork when it comes to data processing. Python has an evolved ecosystem of libraries for machine learning, and you can teach the language far more easily to a statistician than you can teach five years’ worth of statistics classes to a programmer. There’s even a Pybiotics library for robotics, although whether that includes a module for Asimov’s Three Rules of Robotics that ensure the benignity of its creations is harder to establish.

Keep it Simple

Python will teach you to code, possibly more efficiently than any other programming language will. What takes up ten lines of code in C can probably be done with five lines of code in Python. In addition to the mechanics of writing programs for a computer to execute, you’re almost sure to pick up another skill that’s built into the language itself, and which formed one of Guido van Rossum’s prime directives when he constructed the language over that Christmas holiday when he had nothing better to do. The skill is simplicity. Python is not a language for bells and whistles: its code is readable (“readability counts” is one of the aphorisms in “The Zen of Python”) and intrinsically simple (“simple is better than complex” is a further aphorism), and some of that is bound to rub off on you as you learn to translate your computational needs into computer commands. By having Python as your first computer language, you’ll likely learn to bring that simplicity to your programming in other languages when you learn them. That doesn’t mean your C++ code is going to look as elegant on the screen as all those handsome Python indentations, but you’ll have been trained to think in concise terms. That’s a considerable virtue, and not only in programming: the ability to think in simple terms is a valuable rarity in an overcomplicated world.

How Hard is it to Learn Python?

The received wisdom about learning Python is that it is easy to learn and hard to master. Its readability means that you can quickly pick up basic operators and commands and start constructing simple applications in a matter of days.

Even if you don’t have a clue as to the difference between an operator and an object when you start out, basic Python should come quickly to you. To be able to work with some security and range in the language, you should think in terms of months. With considerable application, that can mean as short a time as two months. On the other hand, quite a bit more time is required if you’re to master, not just the syntax, but also many of the vast number of libraries that go with the language. Your knack for syntactical simplicity is also going to have to develop if you’re to be a true expert in Python capable of constructing elaborate applications or artificial intelligence models.

How Long Does it Take to Learn Python?

Longer than the 30-minute Penguin Encounter at the Georgia Aquarium. Not as long as it would take to learn Russian so that you can read War and Peace in the original. You can get a comfortable grasp on the language (Python, not Russian) in about the time it would take you to read Tolstoy’s hefty masterpiece of historical fiction (in English) three times. That comes out to a bit over 100 hours of reading or studying time. Working at Python full-time, you should be able to be reasonably conversant in the language within the space of a month. On the other hand, you’ll need a great deal more time really to master Python, but that will involve, not only class time, but also time spent actually programming in the language. For that, you need to figure at least a year.

Should I Learn Python In Person or Online?

You may be surprised to discover that, today, the overwhelming majority of classes in Python is given online. The days of being about to find several computer schools in every major city have yielded to those schools embracing the virtual classroom and teaching their classes across the internet. The live class hasn’t entirely bitten the proverbial dust as yet, but, if the trend continues, you won’t have much choice in the matter. You may nonetheless find yourself wishing that there were in-person classes like the ones to which school accustomed you when you were growing up. The paradigm of teacher, students, and a blackboard all in the same room dates as far back as the invention of the chalkboard in 1801 and obviously (minus the blackboard) before that, as far back as prehistoric education. That means in-person learning has a few thousand years of human history behind it, so there’s no surprise that you might find it comfortable.

The live online class is, however, remarkably similar to the live in-person class, at least once you get past the inescapable difference that all the participants aren’t occupying the same physical space. While you and your instructor won’t be sharing identical geographical coordinates, you will be occupying the same position in time, which means that you can interact with each other just as you might if you were stationed in the same room. You can ask questions through the time-honored mechanism of raising your hand, and you can even invite the teacher to take a look at your screen to get you through a particularly knotty and unpythonesque bit of code. On the other hand, you get to study in a comfortable spot of your own choosing, without needing to worry about whether your outfit goes together or having to force your way through rush hour traffic from Downtown to Buckhead. You’re spared the concerns of not getting there in time to secure a good seat, and you won’t have to put up with inclement climate control, gum-cracking neighbors, or being seated downwind of someone doused in toxic cologne. Yes, you will have to get used to the new paradigm of following a class on your computer, but, without being overly fatalistic about it, that’s the wave of the future today already, and, like most waves of the future that are here already, this one is inevitable.

An alternative to the live online class is available from many internet-based schools. Termed self-paced, on-demand, or asynchronous, these classes have participants as passive observers of pre-recorded video tutorials. It’s a lecture format, essentially, but it affords no chance for asking questions of the instructor. On the other hand, the convenience of an on-demand class is terrific: you study when and where you want, assuming that there’s a way to link to the internet from where you happen to be. (You can try out the wifi at Read Shop up in Paces; it’s a bookstore as well as a café, and, as such, worth exploring in itself.) Before you get too excited at being able to learn Python with absolute freedom, there are some drawbacks to self-paced learning, probably the weightiest of which is that tutorials go past their expiry dates very quickly, and not all providers of self-paced Python courses are as careful as they should be when it comes to updating their content. You can thus rack your brains trying to learn something that may turn out to be sorely out-of-date. In addition to that, you’re going to need quite a bit of determination to finish a self-paced class without a teacher to guide and encourage you. It can be done, of course, and some people make terrific autodidacts, but, if you’re not good at sticking with things, self-paced online learning probably isn’t the pedagogical method for you.

What Should I Learn Alongside Python?

If you don’t have a background in front end development languages, your Python studies will benefit immensely if you learn the holy trinity of, not celery, onion, and green pepper, but HTML, CSS, and JavaScript. These will give you the ability to create the front ends of websites, and, if you throw in Python’s Flask library, you’ll be able to whip up full stack web applications all by yourself. If you’re after a career in web development, you can’t go wrong with these fundamental front end tools.

If you already know your HTML, CSS, and JavaScript, you might consider learning another language, preferably a compiled one, that will give you an understanding of what other, more involved, languages are like. Starting two languages at the same time is never a good idea, so get a firm grasp on Python before branching out into something else. What that something else should be is a matter of debate, with the primary choices being C# and Java. If there is a consensus on the issue, it would be in favor of C#, which is easier to read than Java (although nowhere as easy to read as Python) and comes complete with libraries and documentation courtesy of the language’s originator, Microsoft. Java, being open source, is a little messier than C#, but it arguably poses a comparable challenge to Python speakers.

Industries that Use Python

Python’s now oft-cited virtues of simplicity, scalability, and ubiquity have spread the language across a wide swath of the Big Peach’s commercial sector. As would befit a city with the busiest airport in the world, and which is headquarters to both UPS and Delta Air Lines, Python is helpful in the development of logistics software. Python’s uses go beyond that, however, and encompass its native terrains of data science and software development, as well as aiding Atlanta’s flourishing financial sector, be it for- or not-for-profit.

Data Science

Perhaps Python’s most pertinent application in the business world is the data science without which today’s businesses wouldn’t know what to do next. That applies to Atlanta’s enormous corporate entities like Home Depot, UPS, and Delta Air Lines, which have entire departments devoted to nothing but this processing of data, down to small companies and even single proprietors who pore over their Google Analytics as though they were a crystal ball. There’s a lot more to data science than Google Analytics, and a combination of Python’s scalability and libraries like NumPy and pandas can turn Big Data into big information.

Software Development

Although there’s been a post-COVID falling off of startups starting up in Atlanta, the city is nonetheless considered one of the up-and-coming tech hubs in the world. That’s garnered the city the not overly creative moniker of Silicon Peach, and definitely has put it on the radar for the all-important funding that makes a startup ecosystem viable. Among the grown-in-Atlanta companies worth noting are Calendly (business scheduling software), Hermeus (hypersonic aircraft), and Patientory (giving patients more comprehensive access to their medical charts.) These show how broad the options are for software developers in the city. All these companies use Python to varying degrees, although its strengths and current popularity make the language an essential component of just about any software project, even if it is only to interpose stickily between portions of programs constructed in other languages such as C and C++.

FinTech

Atlanta is a financial capital on a global scale. Known in some quarters as Transaction Alley, some 70% of all financial transactions in the world pass through Atlanta’s computer networks. That makes Atlanta a major center for FinTech, which is to say the technology of finance. Python is well suited to financial uses, be it for the development of payment systems, financial management tools, or blockchain. All the virtues of Python—its scalability, simplicity, and popularity—apply to all these cases, but perhaps most of all to blockchain, the revolutionary distributed-ledger technology that makes possible cryptocurrencies such as Bitcoin (blockchain was invented as part of Bitcoin’s birth process) and Ether (Python is an excellent choice for the development of smart contracts.) Python’s adaptability to blockchain benefits from more than 500 ready-to-use code packages that can assist in the development of blockchains for cryptocurrency purposes and beyond. One such library even enables the developer to construct virtual blockchains within a cryptocurrency’s blockchain. Python is thus an essential component of FinTech, which, in turn, is an essential component of Atlanta’s overall thriving tech sector.

Python for Nonprofits

Python is employed in a number of ways by nonprofit organizations. The language’s machine-learning capabilities can be harnessed to automate repetitive tasks, such as donor management, email campaigns, and event registration. Not-for-profit organizations and NGOs stand to gain immensely from data science, and, as yet, aren’t squeezing anything like the full amount of conclusions from the data they collect so diligently. Python, as one of the principal languages for data analysis, can come to the rescue here, as, for example, predictive modeling can be used to determine whither a nonprofit should target its fundraising efforts. Atlanta is also home to a number of software companies designed to service nonprofits, such as GiveSmart (bidding technology for charity silent auctions), Double the Donation (matching gifts with companies with gift-matching programs), and TeamWorks (automation for fundraising campaigns.) Also worth noting is that Python itself is a not-for-profit venture, thanks to the Python Software Federation. Those who use the language for profit sometimes remember that they learned it for free essentially, and make efforts to give back to the Python community through pro bono programming projects and similar ventures. Thus, an open-source software project is able to keep giving forward. As would befit, not only the most popular language of the moment, but also an open-source one, Python has distinct value in the not-for-profit sphere.

Python Job Titles and Salaries

Python Developer

Although Python wasn’t created for any especial purpose, and is endowed with formidable number-crunching capabilities, it can also be used as a language for web development. Python Developers work on creating web applications, usually concentrating on the server side of things with a leg-up from Django. The average salary for Python developers in Atlanta is approximately $117,000, which is a bit below the national average of $124,000. Note that U.S. government figures mention the anomaly that, while Computer and Mathematical Operations show employment ahead of the national average for the whole sector, there is a distinct shortfall of people employed in the Web Developer rubric, which can be explained either by Atlanta not being a center for Web Development, despite its title of Silicon Peach, or because there are more jobs than qualified candidates in the Atlanta/Sandy Springs/Roswell statistical area.

Data Analyst

One of the best-known uses of Python is the field of data analysis. Thanks to libraries such as pandas and NumPy and the language’s adaptability to complex mathematical calculations, Python can be used to digest enormous amounts of data to shed light on a company’s (or an investment’s) past performance, and to cast the results into all manner of visualizations that even the most computer-illiterate of managers can understand. Atlanta’s corps of Data Analysts earns an average salary of roughly $81,000 per annum, which outpaces the national average by a small measure.

Data Scientist

Although the terms Data Analyst and Data Scientist (Data Engineer can be tossed into the mix as well) get understandably confused, Data Scientists, strictly speaking, keep their eyes fixed on the future, whereas Data Analysts look back to an organization’s past. Their prognostic abilities account for Data Scientists’ proportionally larger salaries, which, in the Atlanta area, fall out for the most part between $105,000 and $110,000.

Machine Learning Engineers

A different direction in which Python can be taken in the workplace is the development of all manner of machine learning models and applications that can significantly reduce the time programmers, developers, and scientists spend on computing drudgery. Machine Learning Engineers work in a branch of the mushrooming field of artificial intelligence (AI), and their work ties together Python programming, data science, libraries such as Jupyter and Scikit-learn, and data visualization. Salaries for the breed can run quite high, with the United States annual average running to $165,000. In Atlanta, salaries for these workers fall for the most part in the $130,000 to $150,000 range.

Python Classes Near Me

If you’re committed to the idea of an in-person class for learning Python, you’ll find something of an option in the hybrid-type class offered by ONLC Training Centers. This method puts students in a live classroom together with an online teacher who has full access to participants’ computers and operates precisely as a live teacher would. While ONLC does allow for participants to participate from any place they desire, the classroom location does afford a means of accommodating people who would rather go to school by going to school. ONLC’s Atlanta location is in Buckhead, across the street from the Lenox Square Mall. The school is accessible by MARTA and offers a number of nearby options when it gets to be lunchtime. The school provides all necessary materials for the class for students attending in person.

A further option for a live class for beginners with a virtual instructor, is available through Business Computer Skills. The course covers basic coding skills, data types, Boolean expressions, defining functions, program testing and debugging, lists, tuples, expressions, and strings. A follow-up intermediate course goes into advanced programming techniques, while an advanced class teaches Python for data science. Business Computer Skills’ Atlanta area classes take place at their location in Buckhead. Tuition includes all classroom materials and a free retake option.

For live online instruction, you can consider the offerings from Noble Desktop, especially the Python Developer Certificate program, one of the most in-depth offerings in the language available, which, in under a month of full-time study, teaches the language’s coding basics before turning to teaching the Django framework to show you how to program web applications. If you’d prefer to study Python for data science, Noble also offers a Data Science Certificate program that covers using Python together with NumPy and pandas for number-crunching on a grand scale, SQL for querying databases, Python for automation, an extended look at Python for data visualization and dashboards, and, finally, a stop at Python’s machine learning capabilities as they relate to data science. Both these courses include multiple 1-to-1 sessions with a dedicated mentor that may be used however you choose, be it for assistance with classroom topics or job market preparation. Also included is a free retake option (good for one year from the time you complete your class) and access to recordings of your classroom sessions, should you ever want to go over anything a second time.

If you’re in the market for something shorter and more targeted, Noble Desktop offers a Python Programming Bootcamp, an immersive learning experience that will have you programming in the language in under a week of full-time study. The course includes a 1-to-1 bonus training session, along with the retake option and classroom recordings described above.

Available part-time in the evenings as well as full-time is General Assembly’s Python Short Course. In reality, not as brief as some Python course offerings, this class is designed for beginners and covers programming fundamentals, object-oriented programming concepts, and applications of Python for both data science and web development. The course includes a capstone project for students to make practical use of their new skills. Graduates become eligible for alumni events and a discount on future GA courses. Financing is available in various forms, some of them interest-bearing.

Based in Houston, Texas, but with a global footprint, ExcelR is a further purveyor of live online Python instruction. The Python training the school makes available takes students on a journey from variables, operators and loops through to work with libraries such as Django, pandas, and Matplotlib. Included with the course are 24-hour access to trainers for questions, guest lectures and webinars, and a job readiness program. The class may be purchased as a part of a scheme that gives students unlimited access for 365 days to all of ExcelR’s classes, both synchronous and asynchronous.

Python Corporate Training

Although, if you chanced upon a magic lamp and were granted three wishes, you might not choose to spend one on improving your team’s Python skills, you may nonetheless harbor a secret desire that your employees might be more adept at programming in this most versatile and useful language. Whether it be for programming, data science, or even machine learning, greater fluency in Python can definitely increase your team’s effectiveness.

Noble Desktop can help make your Python wishes come true by bringing one of its expert instructors to your company premises for a live in-person class, or by bridging unlimited miles with a teleconferencing platform such as Zoom for a live online class. Noble will work with you to set up a tailor-made curriculum that will improve your team’s Python abilities in precisely the way you desire. If you’d rather take advantage of Noble’s regular roster of Python classes, the school has a voucher program that will allow you to do just that, with discounts for multiple purchases. Feel free to address any questions you might have to Noble’s corporate sales department.

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Key Insights

Learn More About Atlanta Python Courses

What Can You Do with Python Training?

What Will I Learn in a Python Class?

Python

Django

Data Science

Machine Learning and AI

Keep it Simple

How Hard is it to Learn Python?

How Long Does it Take to Learn Python?

Should I Learn Python In Person or Online?

What Should I Learn Alongside Python?

Industries that Use Python

Data Science

Software Development

FinTech

Python for Nonprofits

Python Job Titles and Salaries

Python Developer

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Machine Learning Engineers

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Atlanta Python Courses by School

Emory University

Online Data Analytics Bootcamp (Full or Part Time)

Python Programming Short Course (Online)

Online AI & Machine Learning Bootcamp

Python Programming 2: Advanced Programming Techniques

Python Programming Level 1: Intro for Non-Programmers

Intro to Python Coding for Machine Learning

Atlanta Python Corporate & Onsite Training Noble Desktop

Python Training Locations in or Near Atlanta

Atlanta Careers & Salaries Related to Python

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