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.
This was an amazing course overall and I absolutely loved it!
I would highly recommend this bootcamp to anyone who ever wanted to really understand ML models.
This class offers you the opportunity to refine your Python skills and introduces you to new ways to visualize and, more importantly, summarize data. The project you complete by the end of it will reflect the progress you've made learning Python.
I recommend this course, this teacher, and this school to everyone wanting to learn machine learning. It was an amazing experience.
Excellent coursework and professor. It helped me grasp the basics of machine learning quickly and effectively. The class was hands-on and helped me implement Python concepts and apply them to build machine learning models. It was a great learning experience!
This course is a MUST HAVE and the instructor is GREAT. I recommend taking this course after the Python for Data Science Bootcamp if you never dealt with Python before, or without it if you need a project for your portfolio on GitHub. Both courses were taught by the same great instructor, Art Yudin. Art explains everything very clearly and helps everyone. Right after the course, I got an invitation to interview as a data science intern, and the first thing they asked was to see my projects on GitHub. So I downloaded my final project from this course, and they liked it. They gave me a new one to do, and I found it easy after this course!!!
It was great to see my progress during the duration of this bootcamp. I started with no prior knowledge of Python and by the end of the course, I was able to complete a machine learning project using Python.
Art transfers his knowledge very successfully. The Python Machine Learning Bootcamp included a lot of examples, practice, and possibilities for learning.
Art is a very helpful and patient instructor. I'm amazed at what I can build now.
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!
Very useful instructors and good content. Would recommend the Python Machine Learning Bootcamp.
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.
Rob is extremely knowledgeable and made learning a complicated subject matter more accessible
Really great way to jump into a complicated topic.
I highly recommend this class to anyone that is looking for an intro to machine learning.
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Refresh the materials for free within one year
Attend this course in-person in NYC or Live Online via Zoom. Engage with expert instructors, ask questions, and get feedback on your exercises and projects.
Unlike other providers, these are not mass open-enrollment classes. At Noble Desktop, you’ll learn in small groups (typically 8-15 students) and receive personalized attention.
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.
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.
Our instructors are veterans of their field and experienced educators, driven to help you succeed.
We want you to leverage the skills you’ll learn. In addition to 30 hours of hands-on, small group training, you’ll receive one 1-on-1 training session where you can:
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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We offer a single free retake of the class within a year.
You can also access recordings of each session in your student portal within one business day of the session’s end. Recordings are available for one month after the session.
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).
You have some options:
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.
We don’t currently offer discounts as we do our best to affordably prices our courses.
