Master Python for data analysis, machine learning, and automation. Build predictive models, create dynamic dashboards, and unleash the power of data visualization. Launch your career in data science and Python engineering, equipped with Python, NumPy, Pandas, and Matplotlib.
Learn Python, SQL, automation, and machine learning to become a Data Scientist. Gain Python programming, data analysis, SQL querying, and predictive modeling skills. Perfect for beginners, this program prepares you for entry-level data science and Python engineering roles. Unlock high-paying job opportunities in the field of data science.
Learn the fundamentals of machine learning, including regression analysis and classification algorithms, in this practical, hands-on course. Gain the skills needed to solve real-world problems using machine learning, with a focus on Python programming and data science libraries.
Machines can’t think for themselves, but they are capable of learning. They can learn anything their programmers explicitly tell them to do, and flawlessly retain what they learned. But what happens when there are more things that the computer needs to know than a programmer can input single-handedly? That’s where machine learning comes into the picture. You’ve no doubt noticed how, when texting, your phone somehow develops the knack for suggesting combinations of words you use frequently. Oregano tea, for example, is a highly effective grandmother’s remedy for suppressing coughs, but there is no way that the programmers of your phone would have instructed it to prompt “tea” every time you type “oregano.” That is until the time you had the bad cough and texted all your friends about your grandmother’s cough suppressant: suddenly your phone was prompting you with “tea” whenever you typed “oregano.” The process whereby the computer inside your phone analyzes patterns of data (your text messages) and detects patterns (like “tea” following “oregano”) as a simple example of machine learning.
Just as the computer in your phone can analyze the simple data you input, so can a larger computer be instructed to learn from immensely larger datasets, even datasets that are too large for human beings to manage on their own (so-called “big data”). This type of machine learning is a branch of data science, and part of every data professional’s toolkit. Sooner or later, every Data Engineer and Data Scientist is going to have recourse to this aspect of artificial intelligence.
Machine learning goes beyond just data science (as the cellphone example shows), and there are Machine learning engineers in a growing number of software fields. Knowing how to get computers to learn on their own is a valuable skill, not least of all in a city that combines an established and thriving financial sector with the kind of startup activity that can be seen in Chicago today.
Machine Learning Engineers in Chicago earn an average annual salary of around $155,000, while Data Engineers earn about $125,000 per year. Data Scientists take home average yearly salaries of $120,000, while Data Analysts earn nearly $70,000 annually.
There are two computer schools in Chicago that offer classes in machine learning. General Assembly, located on the Near North Side, offers a Python and Machine Learning Boot Camp that is geared to intermediate users of Python interested in the ways in which the language can be used to create machine learning models. Practical Programming, a school located in the Heyworth Building, teaches a Machine Learning Immersive class, also geared at intermediate students seeking to build their skill sets and apply them to this fascinating area of computer science. Instruction at both these schools is live and in-person.
Although there are schools in Chicago that offer in-person classes in machine learning, many Chicagoans are opting instead to do their studying online: using a machine to learn about teaching a machine to learn, as it were. Online education provides students with considerable advantages, including sparing them the commute through traffic and on crowded public transportation to get to class. Online students also get to learn in the comfort of their own space, free from classroom distractions. On top of that, learning online opens up a wider selection of courses, which constitutes a definite advantage when you’re seeking to study a topic as specific as machine learning.
Despite the fact that online classes don’t put the teachers in the same physical room as the students, instruction is still 100% live and in real-time, meaning that students can ask questions and interact with the faculty in pretty much exactly the same way they could if they were together in the same room. Equally as possible as asking questions is screen sharing and interaction with the other students in the class.
Noble Desktop, the originator of this tool, has several classes that teach machine learning for data science, beginning with a Data Science Certificate program (three weeks full-time, three months part-time) that gives students the tools they need to begin careers as Data Scientists. Noble also teaches a targeted Python for Machine Learning Boot Camp (30 hours of classroom instruction, evenings) that focuses on how the computational powers of the Python computer language can be used to create machine learning models. Finally, Noble teaches a Python Data Science & Machine Learning Boot Camp (66 hours, weekdays) that combines basic training in Python with instruction in how to use its data science libraries (Pandas, NumPy, and Matplotlib) and machine learning techniques to perform statistical analysis.
Machine learning classes can also be taken at NYIM Training. NYC Career Centers offers machine learning courses as well.
Adults aren’t the only ones who can benefit from studying the possibilities of machine learning. NextGen, therefore, provides teenagers with several summer machine learning classes for high schoolers.
Machine learning is only one aspect of the fascinating (and potentially remunerative) field of data science. Those interested in studying the data science big picture will find an exceptionally wide selection of data science bootcamps in Chicago from which to choose. Bootcamps are fast-paced intensive classes that are designed to prepare students for success on the job market. While not for everyone, they can be one of the best stepping stones to a new tech career.
Among the schools offering data science bootcamps of more or less three months’ duration are Metis (located on the Near West Side), the Flatiron School (Near North Side), General Assembly (Near North Side), and Coding Temple (Near North Side). Schools with shorter bootcamps include Practical Programming (in the Heyworth Building) and Data Science Dojo (in the Loop.) A bit outside the city, in Evanston, is the Northwestern Bootcamps Data Science and Visualization Bootcamp (24 weeks, part-time), while the list of online providers of data science bootcamps includes Thinkful and Noble Desktop.
Would you like to improve your existing team’s grasp on the nuances of machine learning? Noble Desktop can offer you a variety of options for corporate onsite machine learning training. Simplest of all, they have a voucher program that will allow your members of staff to attend any of Noble’s regularly scheduled classes. Discounts for multiple purchases are available. Noble is equally as capable of setting up live in-person teaching at your office location with one of their skilled instructors. Or, if you prefer, Noble can also set up virtual live training using a teleconferencing platform such as GoogleMeets or Zoom. Please email Noble’s corporate training department for further information.