Machine Learning on JetBrains Academy
Artificial Intelligence (AI) and machine learning (ML) conjure up images of robots and science fiction movies in many people’s minds, but the fact is they’ve already become an integral part of our society. Are you, too, ready to turn science fiction into reality and get your hands on coding real-world applications based on AI and ML?
With our Introductory Machine Learning in Python track, you can take your first steps in this field of computer science and develop your own machine learning models that find patterns in data and make decisions based on those patterns.
Machine learning in real life
A subfield of artificial intelligence, machine learning involves creating algorithms that can learn from past experiences and then applying that knowledge to new, previously unseen situations.
Machine learning is all around us these days. For example, when you open your mailbox, all the spam messages are automatically filtered to a separate folder. If you receive an email in an unknown language, you can easily translate it to a language you understand in just one click. Your favorite streaming service suggests movies that you’re likely to enjoy. Stores where you shop send you special offers that are relevant more often than not. None of this would be possible without machine learning.
Introductory Machine Learning in Python
The Introductory Machine Learning in Python track is here to give you a clear understanding of the main types of ML algorithms, introduce you to the general pipeline of building an ML model, and give you an idea of what skills and competences it takes to be an ML expert. You will develop a deep understanding of fundamental ML techniques, and you’ll get practical experience with such Python libraries as NumPy, pandas, and scikit-learn.
Projects you’ll build
This track gives you access to more than 160 educational topics and 15 new projects that you’ll create step by step in an interactive learning environment. Let’s take a look at a few of them:
📩 Spam Filter: Build a program that can tell if an email message is spam and filter it out. By completing this project, you’ll learn what Naive Bayes, SpaCy, and pandas are, make use of functions to carry out repetitive tasks and functional decomposition, and implement your own algorithms and measure how well they perform.
🏥 Data Analysis for Hospitals: Data is everywhere, including texts, images, news, and spreadsheets. The amount of data we consume and store is growing by the second. How will you stay afloat in this great sea of data? In this project, you’ll conduct a comprehensive study by uploading datasets, dealing with data omissions and incorrect data filling, finding the main statistical characteristics, and visualizing your data.
📶 Linear Regression from Scratch: Linear regression is one of the most popular methods for estimating linear relationships and one of the most popular ML algorithms. By the end of this project, you’ll have created your own linear regression algorithm, learned about linear algebra, practiced matrix operations, and more.
After you finish this track, you’ll receive a certificate of completion that you can add to your LinkedIn profile and resume. Don’t forget to add completed projects to your GitHub profile as well!
A career to pursue after track graduation
If you’re interested in starting your career as a Junior ML engineer, this track will be right up your alley! Add some knowledge of statistics, data visualization techniques, and SQL, and you can try your hand at working as a Data Analyst or Data Scientist. If any of this sounds interesting to you, or if you want to improve your knowledge of Python in general, get started with the Introductory Machine Learning in Python track!
If you are new to JetBrains Academy, not only can you start a free 7-day trial, but you can also extend it by up to 2 months as you work on your first project! To do that, complete the first stage of your project within the first 7 days and have your trial extended by 1 month. If you finish your first project within that first month, you will have one more month added to your trial.
We hope you’ll enjoy studying machine learning with us. If you have any questions or would like to share your feedback, feel free to leave a comment below or contact us at firstname.lastname@example.org.
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