Live Online vs Online Flex at Data Science Bootcamp Metis

Table of Contents

• Meet Our Expert: Rita Biagioli
• Metis Live Online vs Online Flex
• Data Science as a Career in 2021

Metis transitioned to fully remote learning in 2020 and now students can actually choose to take the bootcamp full-time (Live Online) or part-time (Online Flex). But how should you decide between these two paths? Rita Biagioli, an Instructor at Metis, gives us a tour of the Online Flex classroom, explains the time commitment in the Online Flex bootcamp, and tells us how to choose between the Live Online Bootcamp vs Online Flex Bootcamp at Metis. 

Meet Our Expert: Rita Biagioli

• Rita completed an interdisciplinary Ph.D. focusing on Psychology and Anthropology before shifting into computational social science classes.
• As she transitioned to data science, Rita taught MBAs at a business school while working as a design researcher for the university.
• After discovering an interest in data science, Rita decided to complete a bootcamp program at Metis – and now she’s a resource for students as a data science instructor!

The Metis Online Classroom

Now that Metis is an online bootcamp, how do students choose between the full-time Live Online Bootcamp and the part-time Online Flex Bootcamp?

We launched our Live Online bootcamp in January 2020, before COVID. Launching online was the plan all along and COVID accelerated that. Our goal has always been to reach a wide variety of students and make it convenient for people in all places to reach us and our courses. Our evaluations and metrics are as high as they’ve ever been. 

In late March 2020, we moved to a more modularized format. In Live Online, subjects like regression, deep learning, or engineering are each a two-week module. All of it is streamlined and our bootcamps are made up of these specific sequences of two-week courses. We now also have start dates for each subject course every two weeks, so it’s easy to jump in and get started.

What’s the difference in time commitment between the Live Online and Online Flex for students?

Our Live Online format is totally immersive and it’s great for students who want to work full-time on learning data science. What’s great about our Online Flex format, which is new, is that you can get the same great material, but in a part-time format.

This means that everything you would have to get done in those two weeks of Live Online, for flex, you have four weeks and you can go at your own pace. You don’t have to be online at a specific time, except for meetings with an instructor, which you sign up for, so the times fit into your schedule. You can engage with the content on our platform whenever you’re available. Online Flex is really for students who want to learn data science, but they don’t want to quit their full-time jobs or they want more time to absorb what they’re learning.

Do you have any advice for students trying to choose between Live Online vs Online Flex?

I would think about your learning style and what you know. Some people know that they want to spend a long time thoroughly learning every detail before they move on to the next thing. For those people, Online Flex is a good idea because you have more time to do that. I would think about whether that’s good for you or if you want something more immersive where you’re just hit over the head with it and you have to run fast.

Metis Live Online vs Online Flex

Show us the main differences between Live Online and Online Flex!

Online Flex is built for students so they can take it on a part-time basis. 

In our Live Online format, every course takes two weeks and is full-time. In Online Flex, each course takes four weeks and all of the course content is available on-demand so you can learn on your own schedule. As long as you’re making progress and finishing within those four weeks, you’re good to go. This is great for people who don’t want to quit their jobs or people who want some more time to learn data science.

Those are some differences, but there are also a lot of similarities between our Live Online and Online Flex formats. Both are project-based and both have the same curriculum, which has a proven track record. In both formats, you also get career support until you’re hired.

The bootcamps are a specific sequence of courses that set you up for different careers within data science. We have data analytics, data science, data engineering, and data science and machine learning, and both formats have world-class instructors. 

The main difference is the format, but all of the content you’re going to learn is the same. The best part is, you can take any of our bootcamps Live Online or Online Flex. Everything we offer Live Online, we also offer in the Online Flex format. You have self-paced course content, support from instructors, careers, the whole Metis staff, and the Metis data science community. 

Since Online Flex is self-paced, how do students stay on track and know how to be successful throughout the class?

Let’s talk a little bit about the self-paced course content first. When you log onto our platform for Online Flex, you land on this page with the whole course laid out for you. First, you’ll dive deep into the main goals of the course right away and what your workflow should look like. It also explains the project you’re going to be completing as you go along through the four weeks.

Right from the beginning, your expectations are set and you’re also set up for success, by week. It’s clear when you need to accomplish tasks during the course and what all the lessons are. Overall, we have a nice and clean platform that has all of our great course content in one place.

Give us an example of an Online Flex lesson!

Lessons are where you really learn and internalize the material. In Week Two of the Data Analytics bootcamp, you’ll get an Intro to Pandas (Pandas is a data manipulation package in Python). You’ll have a video lesson to watch and get all of this info about the subject. 

Right away, you can check that you’ve learned with these little Knowledge Check questions that are there to reinforce understanding. 

For many lessons, we also have a coding work-related component to the chapter. You can actually put your knowledge into practice with real coding challenges. These coding challenges mimic what a real data science workflow would look like and lead you through it. They’re not just asking you to write out the code, but they’re also teaching how to put everything into practice in the real world.

All of this work helps to move knowledge from short-term memory into more long-term memory. We have similar lessons with our Live Online group.

Students also do exercises and assessments to reinforce these concepts that you just learned so they get stuck in your head. You’ll often submit work in a Jupyter Notebook. 

Do Online Flex students work on their own projects throughout the class?

Since Online Flex is project-based, students will be working on their very own data science projects throughout the course. Just like in Live Online, our Online Flex students get to pick their own projects and work on what interests them within the confines of the course material.

Students need to submit their project proposals early so that they can work on the project throughout the course. As instructors, we’re always here to help!

What kind of personal support do students have in the Online Flex class?

• One-on-ones – students in Online Flex can meet with an instructor for 30 minutes up to twice a week. This is time to talk about your project proposal, debug your code, and ask any conceptual questions.
• Office hours – weekly office hours are great because you get to interact with your peers and hear questions they’re asking in addition to your own questions. Sometimes that discussion can be important and meaningful in the learning process and Metis careers is always there for you.
• Industry Speakers come to talk about all kinds of topics for advancing your data science career. Oftentimes these are Metis alums and oftentimes the speakers come from companies that are hiring. This support does not end after graduation. All of our alumni are highlighted in our graduate directory on our website.

Is there a way for students to collaborate even though they’re learning online and asynchronously in the Online Flex bootcamps?

Even though we’re online now, community is still a major component of the Metis experience.

We have a Slack workplace just for our Online Flex students and when they’re here they can ask lecture questions, engage with each other, discuss, and call each other. The process of engaging with each other and talking about the material helps to elucidate what you might find unclear, but it also reinforces what you actually know. Of course, if the students can’t answer a question on their own, we can jump in to help. 

Finally, there are all these fun channels like the What’s Cooking channel and the pets channel, people use these a lot. In addition to all the fun stuff on Slack, our awesome program managers are always putting together lunches, coffee breaks, discussions of women in data science, and other times to just chat together. There are so many different ways to connect with your peers in Online Flex.

What’s the biggest lesson your team has learned as Metis has transitioned to more online and modular learning?

We’re always trying to optimize our online learning. We’re constantly making tweaks and instructors are obsessive about making our course offerings as good as possible. Everything’s always changing for the better.

In the past year, we’ve started using a lot of video conferencing with students and a lot of different techniques like polls and whiteboarding. We’re always implementing design choices in our content and our platforms to make sure they reinforce how we want the students to learn. A lot of the structure mimics what working in data science is going to be like. 

Do you have any advice for someone who’s trying to stay on track and get the most out of the part-time Online Flex bootcamp?

I would recommend taking advantage of the resources we offer like making meetings with instructors early. I also recommend writing down your workflows for yourself in advance and even starting to put together a final presentation before you’ve done a lot of the work.

Of course, it’s going to change, but having the presentation outlined lets you see what work you need to do. That’s something that’s easy to put off, but we want you to be thinking about it from the beginning.

Data Science as a Career in 2021

Have students at Metis been landing jobs in 2020 and 2021?

Students are definitely landing jobs; it’s really fulfilling as an instructor to watch students become fully employed data scientists and it happens right after they finish our bootcamps. Everything is picking back up and returning to normal since the pandemic began and I would project that our current students get jobs at comparable rates.

The Careers Team is with you when you’re job hunting, but you also get a full week with them to work on your resume and materials as well as doing mock interviews directly after the bootcamp. 

Do you have any recession-proof job hunting tips for folks that have recently graduated from a data science bootcamp?

Our careers team is an invaluable resource, they’ve been doing this for a long time. The other main thing is to keep going. You need to keep moving forward because if you have the skills, you’ll find a job.

Putting yourself into the world is important and this includes reaching out to employers, writing blogs, and maintaining your GitHub. It’s scary to put yourself on display, but that’s how people are going to see that you have the skills for the job. If you’ve made it through one of our bootcamps, you definitely have the skills.

Why do you think 2021 is the right time to make a career change into data science?

The amount of data in the world is only increasing and we need people who know how to manage it. Since our lives have moved online, there’s even more to track. All industries are beginning to collect data, so there’s growth in the number of positions available. 

I think we’re seeing what misinformation can do and how easy it is to misinterpret data. To some extent, there’s a bit of a moral imperative for us to pay attention to data and what it’s telling us.

Data science is an evolving field and the boundaries are amorphous so it’s easier for someone who doesn’t have direct experience to jump in with relevant experience. The sooner you start trying, the sooner your career starts.

Find out more and read Metis reviews on Course Report. This article was produced by the Course Report team in partnership with Metis.