Python Machine Learning Bootcamp
Master machine learning to create algorithms that can independently learn patterns and make decisions in this hands-on bootcamp.
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30 Hours
NYC or Live Online
Classes are running in-person (socially distanced) and live online. Secure your seat today
Master machine learning to create algorithms that can independently learn patterns and make decisions in this hands-on bootcamp.
Jul 25–Aug 1
Mondays, Tuesday, Wednesday, Friday, 10–5pm
30 Hours
NYC or Live Online
This skillset is in high demand, as machine learning algorithms now run the majority of trading on Wall Street and the product recommendations at big companies like Amazon, Spotify, and Netflix.
This course will begin with linear and logistic regression, the most time-tested and reliable tools for approaching a machine learning problem. The course will then progress to algorithms with a very different theoretical basis, such as k-nearest neighbors, decision trees, and random forest. This will bring important statistical concepts to the forefront, such as bias, variance, and overfitting. You’ll also learn how to measure the accuracy of your models, as well as tips for choosing effective features and algorithms.
The course will be focused on the practical skills needed to solve real-world problems with machine learning. The mathematical foundations for each machine learning algorithm will be explained visually, but there will not be a formal math component. Entering students are expected to be comfortable with writing Python programs, as well as the Numpy and Pandas libraries.
This course does require students to be comfortable with Python and its data science libraries (NumPy and Pandas). If a student has not worked in Python before, we require a student to enroll in our Python for Data Science Bootcamp before taking this course.
This course requires students to be comfortable with Python and its data science libraries (NumPy and Pandas). If a student has not worked in Python before, we require a student to enroll in our Python for Data Science Bootcamp before taking this course.
From our hands-on training style to world-class instructors and custom-crafted curriculum, we deliver results our alumni are proud of.
Python Machine Learning Bootcamp is rated 4.6 stars
in the past 24 months
Excellent. Art fine-tunes his teaching style to our level of understanding. Efficient, patient, current examples of data topics, overall great for me as a beginner - never coded at all prior!
Michelle Moreno
Art is a very helpful and patient instructor. I'm amazed at what I can build now.
Daniel Laserna
Really great way to jump into a complicated topic.
Nolan Young
I highly recommend this class to anyone that is looking for an intro to machine learning.
Marcelo Zampietro
Rob is extremely knowledgeable and made learning a complicated subject matter more accessible
Jason Alter
Tapestry Inc.
EXCELLENT! I was surprised by just how 'inspiring' Patrick turned out to be. He made the material interesting and provided a model of how to establish a good mind-frame necessary to mastery. I loved it. Felt like I got personal direction as well as technical skill.
Sean Kerr
Very useful instructors and good content. Would recommend the Python Machine Learning Bootcamp.
Roberta Caselli
Upon completion of this course, you’ll receive an official certificate testifying to your mastery of the curriculum. We’ll send you a link where you can download your certificate, share it online with your friends, post it to your professional network on LinkedIn, and view all your earned certificates. Congratulations on your achievement!
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Discounts are applied at checkout (no promo code required) and will be verified after you place your order. Discounts are subject to change. Read our discount policies for more details.
As one of our smaller courses, tuition for this course is due in full before the start date. The best way to save on this course is to take it as part of a certificate program.
There are no extra fees or taxes for our courses. The price you see on this page is the maximum you’ll pay us.
However, if you plan to take the course live online, you may need to obtain required software. We’ll help you get set up with a free trial of paid software prior to the class. Most of our coding classes utilize freely-available open-source software. For most of our design and motion graphics courses, we will help you get set up with a free trial of Adobe Creative Cloud. If you attend the course in-person, we will have a computer already set up for you with all of the required software for no additional cost.
Discounts are applied at checkout (no promo code required) and will be verified after you place your order. Discounts are subject to change. Read our discount policies for more details.
185 Madison Ave, NYC
Get face-to-face interaction with an instructor and other students when you learn at our NYC campus. Courses are hands-on with a computer and software provided.
Remote, from anywhere
Get the same interactivity and access to the instructor as in-person students. There are no extra fees and we’ll work with you to ensure your remote setup is perfect.
This class is an 18-hour class that starts by teaching forms of regression analysis and moves onto more industry-used algorithms such as k-nearest neighbors, decision trees, and random forest. Additionally, students will learn how to determine the accuracy of a predictive model.
Noble's typical class ranges from 8-12 students, but we allow up to 20 students to register for our course.
The classes will allow students to learn advanced topics in data science used by the most cutting edge companies such as Google, Facebook, and more. These topics will allow students to build, evaluate, and reassess forecasting models on all forms of data.
Students are not required to complete any work outside of class. However, we provide students with bonus materials if they would like extra practice.
Students will leave with the ability to learn how to build a model from start to finish. Students will learn how to clean and balance data, apply a form of learning algorithm on the data, perform a bias test, and finally evaluate the accuracy of your model.
This course requires students to be comfortable with Python and its data science libraries (NumPy and Pandas). If a student has not worked in Python before, we require a student to enroll in our Python for Data Science Bootcamp before taking this course.
This course does not qualify for payments plans or student financing. See our Payment Plan FAQ to find related programs that qualify.
You may attend this training virtually (online) at the scheduled time the course is offered (New York, Eastern Time).
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Pick up Python fundamentals and quickly transition into analyzing real-world datasets. You will learn to how to clean and combine data, as well as generate useful statistics and visualizations. The final sessions will be focused on using linear regression to extrapolate from data and make predictions.
Master the tools to become a data scientist: Python, SQL, automation, and machine learning. Learn Python programming fundamentals and analyze data with Pandas, NumPy, and Matplotlib, and query databases with SQL. Use machine learning to apply regressions and other statistical analysis to create predictive models.
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