Data Science with Python: Machine Learning

at NYC Data Science Academy

Course Details
$1,890.50 10 seats left
Start Date:

Sun, Apr 23, 1:00pm - May 21, 5:00pm Eastern Time ( 5 sessions )

NYC Data science Academy
Early bird price
Purchase Options
Class Level: Intermediate
Age Requirements: 18 and older
Average Class Size: 18
System Requirements:

You will need a reliable Internet connection as well as a computer or device with which you can access your virtual class. We recommend you arrive to class 5-10 minutes early to ensure you're able to set up your device and connection.

Class Delivery:

This class will be held via Zoom unless otherwise specified

Flexible Reschedule Policy: This provider has flexible, free rescheduling for any-in person workshop. Please see the cancellation policy for more details

What you'll learn in this data science course:

This 20-hour Machine Learning with Python course covers all the basic machine learning methods and Python modules (especially Scikit-Learn) for implementing them. 

The five sessions cover: 

  • simple and multiple Linear regressions;
  • classification methods including logistic regression, discriminant analysis and naive bayes, support vector machines (SVMs) and tree based methods; 
  • cross-validation and feature selection; 
  • regularization; 
  • principal component analysis (PCA) and clustering algorithms. 

After successfully completing of this course, you will be able to explain the principles of machine learning algorithms and implement these methods to analyze complex datasets and make predictions in Python.


  • Knowledge of Python programming
  • Able to munge, analyze, and visualize data in Python


Unit 1: Introduction and Regression

  • What is Machine Learning
  • Simple Linear Regression
  • Multiple Linear Regression
  • Numpy/Scikit-Learn Lab

Unit 2: Classification I

  • Logistic Regression
  • Discriminant Analysis
  • Naive Bayes
  • Supervised Learning Lab

Unit 3: Resampling and Model Selection

  • Cross-Validation
  • Bootstrap
  • Feature Selection
  • Model Selection and Regularization lab

Unit 4: Classification II

  • Support Vector Machines
  • Decision Trees
  • Bagging and Random Forests
  • Decision Tree and SVM Lab

Unit 5: Unsupervised Learning

  • Principal Component Analysis
  • Kmeans and Hierarchical Clustering
  • PCA and Clustering Lab

Final Project

After 20 hours of structured lectures, students are encouraged to work on an exploratory data analysis project based on their own interests. A project presentation demo will be arranged afterwards.

Recommended Readings

  • An Introduction to Statistical Learning, by Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani
  • Applied Predictive Modeling, by Max Kuhn and Kjell Johnson
  • Machine Learning for Hackers, by Drew Conway, John White

Remote Learning

This course is available for "remote" learning and will be available to anyone with access to an internet device with a microphone (this includes most models of computers, tablets). Classes will take place with a "Live" instructor at the date/times listed below.

Upon registration, the instructor will send along additional information about how to log-on and participate in the class.

School Notes: We offer a certification licensed by the NYS Board of Education.

Still have questions? Ask the community.

Refund Policy

Note: This provider has a temporary cancellation policy for COVID-19 related cancellations which is as follows: 

Students receive a full refund of their tuition fees if they cancel their enrollment any time before the first day of the course or if they don't start the course at all (no-shows). We don't charge any registration or materials fee, and there is no charge for transferring to a future session of the course. 


Original cancellation policy (non-COVID-19):

We offer full refund if you are not happy with the first class and decide to drop it.

Start Dates (1)
Start Date Time Teacher # Sessions Price
1:00pm - 5:00pm Eastern Time TBD 5 $1,890.50
This course consists of multiple sessions, view schedule for sessions.

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Questions & Answers (1)

Get quick answers from CourseHorse and past students.

Question from Anonymous
Would this specific class be appropropriate for a person who knows SAS and has good command of statistics?
Answer from Brenda L. CourseHorse StaffCourseHorse Staff
Data Science with Python: Data Analysis & Visualization ( or Introductory Python ( will be more suitable courses to do for your background.

Reviews of Classes at NYC Data Science Academy (31)

(31 Reviews)
Data Science with Python: Machine Learning
Reviewed by Anonymous on 5/17/2021
This was a very good introductory class. The instructor was always available to answer questions in and out of class.
Data Science with Python: Machine Learning
Reviewed by Rachael R. on 10/19/2015
Data Science with Python: Machine Learning
Reviewed by Melanie K. on 10/19/2015
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School: NYC Data Science Academy

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