Key Information
Python Machine Learning Bootcamp
Python for Automation
Python Programming Certificate
$1195 18 Hours
$425 6 Hours
$2795 54 Hours
Overview
Take a step beyond normal programming, into using algorithms that can independently learn patterns and make decisions. Machine learning skills are in high demand, as these algorithms now run the majority of trading on Wall Street and the product recommendations at big companies like Amazon, Spotify, and Netflix.
Learn Python to extract data from websites. Along the way, you’ll learn how to write loops so that your web scraping code can process a large number of pages.
Learn Python programming fundamentals and analyze data with Pandas, NumPy, and Matplotlib. Use machine learning to apply regressions and other statistical analyses to create predictive models.
Prerequisite
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. 
Knowledge equivalent to our Intro to Python Programming or Python for Data Science Bootcamp courses.
Open to Beginners
Location
185 Madison Ave, NYC or Live Online
185 Madison Ave, NYC or Live Online
185 Madison Ave, NYC or Live Online
Scheduling Options
Weekdays & weeknights
Weekdays & weeknights
Weekdays only
Next Start Date
October 19–21, Monday to Wednesday, 10–5pm
September 29–October 1, Tuesday & Thursday, 6–9pm
Oct 12–22, Weekdays
Certification
Receive a Certificate of Completion
New York-licensed Certificate Program
Free Retake Within 1 Year See our class policies for more details
Workbook Included
Courses Included (Certificates only)
N/A
N/A
  • 30 HoursPython for Data Science Bootcamp
  • 18 HoursPython Machine Learning Bootcamp
  • 6 HoursPython for Automation
Discounts See our discounts policies for more details
  • Take 10% off this course if you’ve previously taken any 12+ hour course.
  • Take $100 off this course if you’re an individual paying for yourself (not reimbursed by a company).
  • Shorter courses such as this are already affordably priced and are not eligible for discounts.
  • This is a discounted package of classes that is 15–25% off the individual class prices. Other discounts do not apply.
Payment Plan See our payment plan FAQ for more details
This program is eligible for our “pay-as-you-go” payment plan.
Target Audience
  • Confident python developers who would like to explore machine learning hands-on
  • Developers with strong skills in another language, and some background working with data looking to building machine learning models
  • Employees whose jobs involve any repetitive work in the browser
  • Entrepreneurs running small businesses that need to run efficiently
  • Individuals looking to learn automation techniques for personal or professional use
  • Those interested in a career in automated software testing
Anyone
What You’ll Learn
  • How to clean and balance your data using the Pandas library
  • Applying machine learning algorithms such as logistic regression and random forest using the scikit-learn library
  • Choosing good features to use as input for your algorithms
  • Properly splitting data into training, test and cross-validation sets
  • Important theoretical concepts like overfitting, variance and bias
  • Evaluating the performance of your machine learning models
  • The syntax of Python and how to construct programs
  • How to run your programs on a regular schedule
  • Identify and correct common errors
  • How to write scripts that automate manual tasks 
  • How to update Excel files automatically using Python
  • Analyze tabular data with NumPy and Pandas
  • Create graphs and visualizations with Matplotlib
  • Make predictions with linear regression 
  • Applying Machine learning algorithms to the data
  • Cleaning and balancing data in Pandas
  • Evaluating the performance of machine learning models  
  • Combine information across tables with join statements
  • Advanced techniques such as subqueries and stored procedures 
  • Learn how to write programs in Python to automate everyday tasks