Develop Your Data Science Fundamentals With Metis Admissions Prep

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. 

ENROLL NOW

Upcoming Program Dates

Live Online

Jun 28 - Jul 9

11am - 6pm ET

Next Start | Enroll

Live Online

Jul 26 - Aug 6

11am - 6pm ET

Open | Enroll

Online Flex

Aug 23 - Sep 17

11am - 6pm ET

Open | Enroll

Questions?
Schedule a Call

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

ENROLL

An Online Experience that Brings the Classroom to Life

Live Online | 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.

WHICH SHORT IMMERSIVE FORMAT WORKS FOR YOU?

Whether you choose Live Online or Online Flex, you’ll be on the fast track to upskilling in Linear Regression and Web Scraping.

LIVE ONLINE FORMAT

Master a new topic—quickly—with an immersive, full-time, two-week format. Live Online lectures let you interact with instructors and peers.

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

Live Online: $3,500

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.

TALK WITH US

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.

  • Kimberly Fessel

    Lead Data Scientist

  • Joe Eddy

    Senior Data Scientist

  • Chris Bruehl

    Data Scientist

Meet the Full Team

AVG RATING
4.89
AVG RATING
4.8
AVG RATING
4.91

Upcoming Program Dates

Live Online

Jun 28 - Jul 9

11am - 6pm ET

Next Start | Enroll

Live Online

Jul 26 - Aug 6

11am - 6pm ET

Open | Enroll

Online Flex

Aug 23 - Sep 17

11am - 6pm ET

Open | Enroll

Questions?
Schedule a Call

Frequently Asked Questions

  • Are there prerequisites for the Linear Regression for Web Scraping short immersive course?

    In order to get the most out of the course, students should be comfortable with the mathematics fundamentals of machine learning including linear algebra, calculus, statistics, and probability. Additionally, students should be proficient in general pandas, Python, and basic visualization libraries, and be able to use these tools to explore, analyze, and visualize tabular datasets. 

    All students will also need an account on Github, the web-based hosting service for version control using Git. It’s fast, free, and easy, to sign up.

  • How do I enroll in the Linear Regression and Web Scraping course?

    To enroll, simply click here. Enrollment for the course closes at 8pm ET on the Friday before the start date to help ensure students receive the information they need to join the class on day 1.

  • How much does this course cost? Are there payment options?

    Tuition for the Linear Regression and Web Scraping course is $3,500 for the Live Online format and $2,500 for the Online Flex format. Students can pay for the course in full or consider one of our financing options. We partner with Ascent to offer monthly repayment options for our students. Learn more by visiting Ascent.

  • How much time is required to take this course?

    The live online course format requires a full-time commitment Monday through Friday for two weeks during the hours of 11:00 am - 6:00 pm ET / 10:00 am - 5:00 pm CT / 8:00 am - 3:00 pm PT. The daily schedule includes lectures, pair programming, independent project work, and a one hour lunch.

    Additionally, students should expect to spend additional time each night reviewing lectures, completing assignments, and working on their course project. In order to receive their certification of completion, students must maintain attendance and achieve passing scores on both the project and assessments.

    The Online Flex short immersive course format, requires a commitment of 15-to-20 hours a week for four weeks. Students watch on-demand lectures and engage with instructors and teaching assistants live online during 1:1 sessions weekly.

  • Do I have access to Metis Career Support through the Linear Regression and Web Scraping course?

    No, we do not offer career support for avocational course students like we do for our bootcamp students. However, students will gain access to our always-expanding network of data professionals and to job opportunities and networking events that we routinely post in Slack.

  • Who is the Instructor for this course?

    Our highly qualified, industry-experienced instructors at Metis teach both our short-immersive courses and our bootcamps. Their expertise and educational experiences span healthcare, physics, business, engineering, neuroscience, and more.

ADDITIONAL FAQ

Questions?

Read our FAQs

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