Machine Learning Immersive

at Practical Programming - Chelsea

Course Details
$1,250 5 seats left
Start Date:

Mon, Oct 28, 10:00am - Nov 01, 5:00pm (5 sessions)

Next start dates (2)

Chelsea, Manhattan
115 W 30th St 5th Fl Ste 501
Btwn 6th & 7th Avenues
New York, New York 10001
Purchase Options
Class Level: Beginner
Age Requirements: 18 and older
Average Class Size: 15
Teacher: Timothy Peach

What you'll learn in this machine learning course:

In this course, you will learn the fundamentals of Machine Learning and reinforce these concepts by working with real data and building meaningful predictive models. 

Afterwards, you will have a portfolio where you can showcase your projects, and the necessary foundation in Machine Learning to continue in a direction that best fits your interests and skillset.


If you are aspiring programmer, whether beginner or jedi, this course is for new learners on the pursuit to master machine learning concepts. 

This course discusses the FUNDAMENTAL principles of machine learning. No prior machine learning experience necessary. 

The programming language we’ll be using is Python, the leading language for Machine Learning. 

You should already have some experience coding in Python, but you don’t have to be a professional programmer. 

If you’re completely new to Python, we offer a Python Immersive course which will give you the tools you need to get started with Machine Learning Immersive. 

On the first day, we’ll shore up our fundamentals in Python with a review, and then begin the dive into Machine Learning.

You will learn:
  • Review of Python Fundamentals
  • Python Libraries: Pandas, Sci-kit learn, and Matplotlib
  • Supervised Learning Models (Regression and Classification)
  • Unsupervised Models (Clustering)
  • Data Cleaning and Standardizing the Data
  • Exploratory Data AnalysisFeature Engineering
  • Modeling Fundamentals: Train/Test Split, Cross validation, Underfit and Overfit, the Bias-Variance Trade-off
  • Interpreting the Results of Machine Learning ModelsPutting your projects on Github (can act as a portfolio)

Typical studying day starts at 10am with a previous day recap and completing previous exercises. Lecture on new topics takes about two hours and starts at 11.00am. After lecture, students start working on new exercises with instructor guidance. Around 3pm students present and discuss their work with instructors, learn alternative solutions, and best practices from instructors and invited professional programmers.

Prerequisites & Preparation:
  • Python Programming 101
  • Laptop

Still have questions? Ask the community.

Refund Policy
If you withdraw two days before the course start date, any deposit paid will be refunded in full. 

No refunds will be given for cancellations made after that date. If you cannot attend our class or workshop, for which you were charged, you will receive 25% discount for any other course.


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All classes at this location

Start Dates (3)
Start Date Time Teacher # Sessions Price
10:00am - 5:00pm Timothy Peach 5 $1,250
This course consists of multiple sessions, view schedule for sessions.
Tue, Oct 29 10:00am - 5:00pm Timothy Peach
Wed, Oct 30 10:00am - 5:00pm Timothy Peach
Thu, Oct 31 10:00am - 5:00pm Timothy Peach
Fri, Nov 01 10:00am - 5:00pm Timothy Peach
10:00am - 5:00pm Timothy Peach 5 $1,250
This course consists of multiple sessions, view schedule for sessions.
Tue, Nov 19 10:00am - 5:00pm Timothy Peach
Wed, Nov 20 10:00am - 5:00pm Timothy Peach
Thu, Nov 21 10:00am - 5:00pm Timothy Peach
Fri, Nov 22 10:00am - 5:00pm Timothy Peach
10:00am - 5:00pm Timothy Peach 5 $1,250
This course consists of multiple sessions, view schedule for sessions.
Tue, Dec 17 10:00am - 5:00pm Timothy Peach
Wed, Dec 18 10:00am - 5:00pm Timothy Peach
Thu, Dec 19 10:00am - 5:00pm Timothy Peach
Fri, Dec 20 10:00am - 5:00pm Timothy Peach

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Questions & Answers (3)

Get quick answers from CourseHorse and past students.

Question from anonymous
Did anybody sit through the class? 7 hours of sitting...sounds pretty crazy.
Answer from Art Y. Verified Educator
Machine Learning Immersive is not about lectures, this is not a history class. Machine Learning Immersive is about how to build stuff on your own, it is a constant process of lectures, guidance, debugging and hard work.
Answer from anonymous
Sounds like you're selling snake oil.
Show all 2 answers
Question from anonymous
What is the instructor's background in Machine Learning? Has he worked on data projects before, has he taught the subject? Are there course materials we can take home?
Answer from anonymous
We will provide you with written materials and Python code examples as an online coursepack.
Question from anonymous
Do these guys even have a background in machine learning?
Answer from Art Y. Verified Educator
Timothy Peach is a Python developer and computer science teacher. He has worked in consulting, providing data-driven solutions, and has skills in machine learning, data visualization, algorithms, and AI.
Answer from anonymous
It seems like he has two months experience. He's a beginner himself. How do you expect him to teach the class?
Answer from Art Y. Verified Educator
There are two instructors teaching all Immersive classes, Timothy is one of them. Currently there are six instructors teaching at Practical Programming. Our main advantage is that all instructors have daytime jobs and bring best practices from real life to the classroom. Please visit our website at for more information.
Answer from anonymous
Yes it shows he has two months of experience on his LinkedIn page. Thanks!
Show all 4 answers

Reviews of Classes at Practical Programming (348)

(348 Reviews)
Machine Learning Immersive
Reviewed by Anonymous on 10/19/2018
The Machine Learning immersive course is a fantastic class for anyone with some fundamental knowledge of Python looking to get into machine learning. The first 2 days of the class focus on Python revisions. On day 3, you start learning about pandas, numpy and matplotlib and get to practice by running a lot of models (both supervised and unsupervised). There is also some introduction to deep learning techniques (neural networks) though there won't be a ton of time to practice it, but at least you'll know what it is. Tim, the instructor is a fantastic teacher - he has a strong handle of the material and takes cues from his class: he will speed up or slow down when it's needed and always make sure everyone in his class is following along. If you're interested in machine learning and have some knowledge of Python, this is the class for you!
Machine Learning Immersive
Reviewed by Anonymous on 2/16/2019
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