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Duration

10 weeks

Tuition

$3,100

 

Aug 8-Oct 19

Commitment

Part-Time

Delivery

Live Online

Credential

Certificate

Year Founded

2011

Scholarships

yes

Create robust predictive models with statistics and Python programming. Build confidence and credibility to tackle complex machine learning problems on the job. Thousands of companies need team members who can transform data sets into strategic forecasts. Meet that need. Learn to apply machine learning techniques to fuel predictive models like customer segmentation and recommendation engines.

General Assembly’s best-in-class curriculum is designed with – and for – Data Professionals. Concentrate on the most important tools for data scientists on the job. GA’s data science advisory board regularly curates the best practices and innovative teaching approaches of their entire expert network to emphasize real-world relevance and meet evolving employer demands. Its work ensures that students graduate ready to tackle the challenges they’ll face in the field.

Tailored for students with quantitative or programming backgrounds, this course dives into the essentials of data science: Python programming, exploratory data analysis, data modeling, and machine learning. Get the hands-on experience you need to synthesize extremely large data sets, build predictive models, and tell a compelling story to stakeholders.

You’ll get a head start with pre-course prep lessons. Once you enroll, General Assembly will equip you with an additional 25 hours of online, self-paced preparatory lessons to set you up for success. Dive into the fundamentals of Python programming, statistics, and applied math. You’ll gain a common vocabulary to start collaborating with classmates on day one.

With General Assembly, you’ll get individualized instructor support with guidance, feedback, and more from experts who are dedicated to supporting your learning and career goals. Instructors are on hand in class and during office hours to offer real-time technical assistance and help you turn ideas into action.

Graduate with a polished capstone project that uses machine learning to solve a data problem. Develop a predictive model, technical documentation, and stakeholder presentation.

 

Ready to get started?

Next Cohort: Aug 8-Oct 19

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Student Reviews (8)

General Assembly

Top instructors and classmates

Sam Boman

June 28, 2022

Graduated From

Software Engineering Immersive

Overall:

5 out of 5

Instructors:

5 stars

Curriculum:

5 stars

Job Assistance:

5 stars

Fast-paced course with exceptional instructors who are hired for their expertise and passion. They are in your court and want you to succeed! Same goes for the Teaching Assistants who are an important part of the teaching experience. My favourite part ...

Fast-paced course with exceptional instructors who are hired for their expertise and passion. They are in your court and want you to succeed! Same goes for the Teaching Assistants who are an important part of the teaching experience. My favourite part of the program is actually the Slack channel with all of the students. It's basically active all the time with fellow classmates trouble shooting and sharing opportunities and ideas. The workload isn't crazy once you get into the second-third week, but was overwhelming at first. Highly recommend this life-changing learning experience!

General Assembly

Data Science Immersive (Toronto) Review

Garry

Toronto • May 5, 2020

Graduated From

Data Science Immersive

Overall:

4 out of 5

Instructors:

5 stars

Curriculum:

5 stars

Job Assistance:

3 stars

Through my experience at General Assembly (note, when I started, it was still Bitmaker, but in effect, the content was General Assembly approved), I was able to land my first data science role.

While the industry is hiring Sr. Data Scientist en...

Through my experience at General Assembly (note, when I started, it was still Bitmaker, but in effect, the content was General Assembly approved), I was able to land my first data science role.

While the industry is hiring Sr. Data Scientist engineers, and Sr. Data Scientists, breaking in is difficult for more entry-level Data Analyst/Scientists. However, I do like how there are Data Scientists who come from a variety of backgrounds, from social sciences, cognitive sciences, to mathematics.

On this journey, I’ve had a lot of support from my General Assembly instructor (Max is one of smartest, and also most effective teachers), career coaches and classmates.

Note, your mileage may vary based on your instructor, or peers (to drive discussion and helping each other). I was lucky to have one of the best. Our instructor worked at two local start-ups before joining General Assembly, so he had real experience. Additionally, he often presented at conferences like Pycon and abroad. This is the by far the reason why I am rating General Assembly so high, it’s because you gain access to an instructor who can teach the material better than online materials. Anyone can find a Jupyter notebook on Random Forests, or youtube video on Neural Networks, but to get insights from an Engineer who has written production code, and has advice about ‘flex’ topics like why Docker, cloud computing, and a better way of approaching a problem is invaluable.

Choose your boot camp based on your instructor. That’s the differentiating piece. Go to an info session, and ask him/her questions.

Coming from the software industry previously, the inclusiveness and culture were great, but not a differentiator for me. I’d imagine Brainstation being similar. But those guys were way too sales-y while recruiting, which is why Brainstation turned me off. The syllabus was a bit less relevant too.

To close I’d like to highlight two areas of improvement.
- It’s a jam-packed 12 weeks, but if there was a way to embed more data engineering, software engineering by removing some of the less relevant algorithms, I think that would be better time spent.
- Career support is great, but let’s raise the bar for those who have already worked in the industry. The general advice is table stakes (geared towards interns and university students), so it would be more valuable to have real data scientists, and data engineers provide advice on how they recruit, and perform whiteboard interviews. The network of alumni is growing, but the corporate partnerships engagement is weak as far as student employment is concerned. The career coach is working hard on early conversations with Telus Digital and MaRS, but at this point, there’s no real pipeline to feed students into those programs. Bet on yourself to find jobs rather than rely on employers knocking on your door on demo day. Set your expectations appropriately.

FAQ

  • How do I secure my spot in a course?

    To ensure all GA students get the individual attention and resources they need to succeed, course sizes are limited. After submitting their applications, students connect with an admissions rep, who determines whether or not the course is a fit for their experience and goals. Additionally, applicants for our full-time Immersives complete admissions assessments to ensure they are prepared for the rigor of the curriculum. Once you’ve been accepted and have put down your initial down payment, your spot in the course is secure. Request a course package to learn more.

  • Do you offer payment plan options?

    We understand these courses are a significant financial investment, so we provide several options to ease tuition payment. After submitting a down payment to save your spot in the course, you can choose the installment plan that’s best for you. Additionally, we work with financing partners to offer low-cost loan options for eligible students. Another fun fact: More than 45% of our part-time students receive tuition reimbursement for their GA education via employer sponsorship.

  • I’m an absolute beginner with zero experience or knowledge in the subject matter you teach (e.g., web development, digital marketing). Are your courses still for me?

    Many of our long-form courses are geared toward beginners and no prior knowledge of a subject is required. Additionally, these courses often feature pre-work assignments to get you up to speed with essential concepts and tools. Inevitably, our courses attract students with a wide variety of backgrounds and expertise, so we make sure to have instructional associates, office hours, and additional help available as needed to provide personalized feedback and support.

  • Besides the hours spent in class each week, how much time do I need to dedicate to a course outside of the classroom?

    It varies by course and by person, but, as a part-time student, be prepared to work hard and dedicate several hours outside of the classroom each week to review course material and complete homework assignments. Our full-time Immersive students also devote additional time to portfolio projects, networking events with hiring partners, career services support, and more. Either way, our courses are designed to be rigorous and intensive, but, most of all, incredibly rewarding!

  • What if I really want to take a GA course but just can’t afford it?

    Good news: You’ve got options. More than 45% of our part-time students receive tuition assistance from their employers. Ask your local Admissions rep for information to share with your manager about our courses and the benefits they can provide your company. We also work with financing partners to offer low-cost loan options for eligible students.

  • What is your cancellation and refund policy?

    GA’s campuses are governed by location-specific regulatory standards that we must comply with regarding refunds. For this reason, our refund policy varies based on your location while taking a GA course. Request a course package to learn more.

  • What will the Remote Immersive experience be like?

    We know it can be hard to focus while learning online. Given the number of real-life and online distractions that may keep you from your work, we’ve designed course activities that keep you engaged and in constant conversations with your fellow classmates, instructors, and instructional associates. Our lessons are broken up into micro-lectures, which introduce content in short spurts. You’ll then work individually, in pairs, or in groups to apply what you’ve learned. We also encourage students to interact independently so they can get to know one another better and build a sense of community.

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