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MACHINE LEARNING CLASSIFICATION COURSE

Master Machine Learning Classification in Two Weeks

The Metis Short Immersive Course for Machine Learning Classification will equip you with in-demand skills so you can leverage classification methods to solve real-world problems. You’ll join daily live online classes and complete the course in just two weeks. 

ENROLL NOW

Upcoming Program Dates

May 3 - May 14

11am - 6pm ET

Next Start | Enroll

Jun 1 - Jun 11

11am - 6pm ET

Open | Enroll

Jun 28 - Jul 9

11am - 6pm ET

Open | Enroll

Questions?
Schedule a Call

Build Sought-After Machine Learning Skills in Two Weeks

Our Short Immersive Course will teach you to apply machine learning (ML) classification skills that companies value more and more each day. Put yourself ahead of the curve—and the competition.

Learn from
Experienced Data
Science Instructors

Your course is taught by industry-seasoned teachers who meet a high bar of instructional excellence.

Complete a
Professional Portfolio
Project

You will be required to design and complete a project to showcase your ability to apply your knowledge.

Quickly Build Skills
with Immersive
Learning

Pick up in-demand skills quickly with our immersive daily classes that you’ll take over two consecutive weeks.

Be a Part of a
Professional Network

Skill-building isn’t the only benefit of taking a Metis course. You’ll join a far-reaching community of data science professionals.

Machine Learning Course Overview

MACHINE LEARNING CLASSIFICATION COURSE

Week 1

Classification Basics

We’ll start with the basics. Week one of this ML online course is about getting acquainted with classification models and metrics. We’ll also cover feature engineering for classification problems.

Week 2

Classification Advanced

In week two, we’ll dive deeper into classification models and how to work with imbalanced data sets. At the end of the course, you’ll present a final project.

PROJECT

Apply your new skills by choosing a realistic classification problem to solve using a real world dataset. You’ll do this by using algorithms such as logistic regression, decision trees, random forest, gradient boosting, KNN, and more. Dive deeper into techniques for supervised machine learning, address the difficulties of class imbalance, and determine the proper metrics for your modeling problem.

What's Covered

  • How to explain the theoretical underpinnings of common classification algorithms, including their assumptions and limitations
  • The merits of each classification algorithm in terms of predictive performance, interpretability, and complexity
  • Calculating key metrics used to evaluate classification models
  • Identifying appropriate use cases for each classification metric
  • Ensembling, hyperparameter tuning, and class imbalance strategies to improve classification performance
  • Applying classification concepts to real-world business problems

Prerequisites

We recommend that you have a basic understanding of:

  • Pandas, Python, and basic visualization libraries, and the ways these tools are used to explore, analyze, and visualize tabular datasets
  • Mathematics fundamentals of machine learning including linear algebra, probability, calculus, and statistics
  • Linear regression theory and its applications
  • Basic concepts in machine learning, including regularization, supervised learning terminology, gradient descent, bias/variance trade-off, and evaluation and model selection techniques

ENROLL

Learn From Elite Data Scientists

Our Machine Learning Classification Course is led by experts in the field with superior online teaching experience. Read up on a few of our industry-seasoned instructors now.

  • Vinny Senguttuvan

    5 years at Metis

  • Joe Eddy

    3 years at Metis

  • Kimberly Fessel

    2 years at Metis

Meet the Full Team

An Engaging Live Online Experience

Join us for class—wherever you have internet connection. We’ll deliver an interactive, in-depth experience you can’t replicate on your own.

Stay engaged and follow along as your instructor shares a presentation.

Join the conversation on video, in the chat, and with the polling feature.

We simulate the in-person learning experience with a digital whiteboard.

You’ll collaborate with your classmates during project work and pair-programming.

Keep up with your teachers and classmates in your dedicated Slack channel.

AVG RATING
4.89
AVG RATING
4.8
AVG RATING
4.91

Payment Options

TUITION COST

Pay your course tuition up front: $3,500

FINANCING OPTIONS

Coming soon! Finance your tuition through our lending partners: Skills Fund and Climb Credit.

EMPLOYER SPONSORSHIP

Find out if your employer will cover the cost of tuition to support your development.

CONSIDERING OUR IMMERSIVE DATA SCIENCE BOOTCAMP?

Short Immersive Course alumni can apply the amount of tuition paid for one course towards enrollment in an upcoming bootcamp upon admittance.

Upcoming Program Dates

May 3 - May 14

11am - 6pm ET

Next Start | Enroll

Jun 1 - Jun 11

11am - 6pm ET

Open | Enroll

Jun 28 - Jul 9

11am - 6pm ET

Open | Enroll

Questions?
Schedule a Call

Frequently Asked Questions

  • What are the prerequisites for the Machine Learning Classification short immersive course?

    The Machine Learning Classification short immersive is an advanced course, and while anyone can enroll, we strongly recommend students only enroll if the following applies to them:

    • - Comfort with the mathematics fundamentals of machine learning including statistics, calculus, probability, and linear algebra.
    • - Proficiency in general pandas, Python, and basic visualization libraries and an ability to use these tools in order to explore, analyze, and visualize tabular datasets.
    • - Familiarity with the theory and applications of linear regression.
    • - Understanding of foundational concepts in machine learning, including supervised learning terminology, regularization, bias/variance trade-off, gradient descent, and model selection and evaluation techniques such as cross validation and testing.
    • - Comfort with web scraping or obtaining data through application programming interfaces (APIs) is a definite plus for expanding the range of possible projects a student can complete, but is not strictly necessary to succeed in the course.
    • - Lastly, students will need a Github account. It’s free and easy to sign up. 

  • How do I enroll in this course?

    Click here to enroll in the Machine Learning Classification short immersive course. Enrollment will close at 8pm ET on the Friday before the class start date to guarantee students receive the information they need to start class on the first day.

  • How much does this course cost, and are there payment options?

    Tuition is $3,500, and students pay in full upon enrolling.

  • What kind of the time commitment does the Machine Learning Classification course require?

    Full-time, Monday through Friday for two weeks. In order to successfully complete the course and receive a certificate of completion, students must maintain attendance daily from 11:00 am - 6:00 pm ET / 10:00 am - 5:00 pm CT / 8:00 am - 3:00 pm PT. These hours include lectures, pair programming, a one-hour lunch break, and independent project work. Additionally, students will spend time outside of class completing assignments, reviewing lectures, and working on their course project.

  • If I enroll in this course, do I get access to Metis career support?

    No, we do not offer career support for our short immersive course students. But our immersive course students do gain access to our network of data professionals, and to networking events and job opportunities that are shared in Slack.

  • Who teaches the Machine Learning Classification course?

    Metis short course Instructors are the same ones who teach our bootcamps. Their expertise spans engineering, physics, healthcare, business, neuroscience, and more.

ADDITIONAL FAQ

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Want Something a Little More In-Depth?

The Metis Bootcamps are designed to immerse you in a range of topics and skills needed to start a career in data science and analytics. Plus, you will get career support from industry-seasoned experts.

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