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LINEAR REGRESSION AND WEB SCRAPING ONLINE COURSE

Build Linear Regression and Web Scraping Skills

The Metis Short Immersive Course for Linear Regression and Web Scraping will equip you with the knowledge, skills, and techniques to solve advanced business problems using data. 

Upskill Fast

Companies use linear regression to enhance their forecasts and make better decisions that impact profitability. Web scraping is used to gather unique, insightful datasets that are difficult or impossible to access with conventional means. See how this Short Immersive Course will equip you with these valuable skills.

Learn from Expert
Data Scientists

Our industry-seasoned teachers meet the highest bar of instructional excellence.

Apply Your Learnings
with a Project

Every Metis student designs and completes a project that shows off their just-learned knowledge.

Build Skills Quickly
with Immersive
Classes

You’ll learn real-world skills quickly thanks to our immersive classes.

Network with Data
Professionals

Taking this course goes beyond skill-building. You’ll network and keep up with an extensive community of data science professionals.

Linear Regression and Web Scraping Online Course Overview

LINEAR REGRESSION AND WEB SCRAPING COURSE

Unit 1

Linear Regression Basics and Web Scraping

We’ll start with the basics. Unit one is about getting acquainted with linear regression as well as feature engineering and cross-validation. In addition to these topics, you’ll learn web scraping basics.

Unit 2

Linear Regression Advanced

In unit two, we’ll dive deeper, covering topics like regularization and stochastic gradient descent. You’ll also learn time series regression methods. At the end of the course, you’ll present a final project.

PROJECT

Apply the skills you’ve just learned by solving a linear regression problem. You’ll web scrape to gather data, go deep into regression theory, and practice using python modules like scikit-learn. Finally, you’ll demonstrate your ability to use foundational machine learning techniques like feature engineering and cross validation.

What's Covered

  • Machine learning terminology and how to describe modeling applications, matching different modeling approaches to their appropriate use
  • How to relate the theoretical concept of predictive model complexity to model building and tuning in practice
  • Describing and applying model selection and evaluation techniques, including validation, cross-validation, and testing
  • The purpose and applications of Python web scraping libraries, including their respective strengths and limitations
  • Leveraging web scraping to navigate HTML hierarchy and extract information from it
  • Regularized linear regression, including its relationship with the bias/variance tradeoff, regularized cost functions, and the major practical differences between LASSO and ridge regularization
  • Data handling and pre-processing techniques leveraged by linear regression models
  • Interpreting visual information to gain insight into feature-target relationships and generate feature engineering ideas
  • Applying linear regression concepts to real-world business problems

Prerequisites

We recommend that you have a foundational understanding of the following:

  • The basic visualization tools used to explore, analyze, and visualize tabular datasets
  • Python and pandas
  • The mathematics basics of machine learning from calculus to linear algebra

An Online Experience that Brings the Classroom to Life

Online Flex

Experience what a lecture is like and how you’ll participate during class.

On-demand lectures let you study at your own pace.

Follow along during lecture as your instructor shares their screen.

Clear deadlines and structured modules keep you on track.

Interact with your instructors and classmates on video, in the chat, and with the polling feature.

Deepen your learning with interactive exercises to test what you’ve learned.

Real-time whiteboarding simulates the classroom learning experience.

Connect with peers in the learning platform and via Slack, and attend office hours with your instructor.

Collaborate with classmates during pair-programming, project work, and more.

Attend live speaker presentations, social events, and more.

Chat with your instructors and classmates in a dedicated Slack channel.

LEARN MORE ABOUT OUR SHORT IMMERSIVE FORMAT

Our Online Flex program will have you on the fast track to upskilling in Linear Regression and Web Scraping.

ONLINE FLEX FORMAT

On-demand lectures give you all the flexibility you need. Assignment deadlines and 1:1 instructor support keep you on track, and organized modules provide you with structure.

Length

Tuition

Weekly Time Commitment

Schedule

Lectures

Instructors

Office Hours

Project Presentations

Social Activities

Payment Options

PAY UP FRONT

Online Flex: $2,500

FINANCING OPTIONS

Coming soon! Finance your tuition through our lending partner: Ascent.

EMPLOYER SPONSORSHIP

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

Our Elite, Engaging Instructors

The Linear Regression and Web Scraping Course is taught by deeply knowledgeable, industry-seasoned instructors. Meet some of the team below.

  • Rita Biagioli

    Data Scientist

Meet the Full Team

Frequently Asked Questions

ADDITIONAL FAQ

Questions?

Read our FAQs

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A Metis Short Immersive Course will take you far, but our bootcamps will take you further. Explore more than just a few topics and get in-depth, dedicated career guidance.

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