You can easily become a Data Scientist or Machine Learning Engineer or Artificial Intelligence Scientist in this day. There are several options for both in-person classes and online classes. Almost no program is structured alike (even though most of the syllabus is similar). The barrier to learn, discover is extremely low, however, there is definitely a high barrier to complete, consolidate and apply these learnings in real life. I noticed that there are several programs out there, one way to slice and dice various programs is based on the tuition fees, part 1 of the blog focuses on courses over USD $1000 and part 2 of the blog focuses on courses less than $1000. Since there are a lot of courses out there I only reviewed the ones that have more than 100,000 hits on the site (or Alexa rank <1000). I know this might not be a great threshold to evaluate courses but I couldn’t come up with a better metric (perhaps students placed would be a great indicator, but I couldn’t find publicly available numbers for that)
My first recommendation is Lambda School. The school took ISA (Income Sharing Agreements) to a whole new level mostly championed by their charismatic founder Austen Allred.
The company was founded by Austen Allred & _____ and is from the Y Combinator Winter 2016 cohort. They have so far trained over 800 data science students (the first batch of Data Science students seems to be from 2019 summer, and by their own course completion report over 27% have gotten jobs (which is actually a pretty decent number).
The course is completely online, they have two options;
a) Full-Time: 5 days a week from 9 am — 5 pm PST
b) Part-Time: 4 days a week 6 pm — 9 pm
The full-time Data Science program runs for 6 months while the part-time Data Science runs for 12 months.
They have two options, either pay upfront USD 30000 (or $15000 depending on your state, which is weird) or pay 17% of your salary (again only if it is greater than $50,000/year following Lambda graduation) of the first two years of your job (capped at USD 30000), this is actually a great model. But you must be a US citizen of GreenCard holder (not sure why they didn’t include folks who are authorized to work in the US such as H1B, L1, considering those engineers also make a sizable group). For all others such as international students, you must pay USD 15000.
Their USPs include:
- ISP (students literally pay $0 upfront and only pay on placement, huge alignment of interests)
- Live sessions (all the sessions are live, they aren’t self-paced)
- They have an extremely strong career development track
- Their curriculum is divided into modules & sprints, this is actually very smart. Sprints
- The class sessions are called Guided Project. The assignments are auto-graded (by Codegrad) and extremely similar to these.
- The Career Track module is incredibly solid, they take it extremely seriously. I haven’t seen another institute take it this rigorously. Which makes total sense as Lambda only gets a fee when the student gets placed. They go the extra length to help you craft your resume, LinkedIn, GitHub, strengths, weaknesses, etc. Basically, help you set up for success in a job search. Job search in itself is an extremely arduous task! I found lots of candidates with excellent technical skills who couldn’t really communicate but would struggle in getting jobs (maybe Lambda should be spun off into a separate course as I found this to be incredibly helpful!)
- The faculty is generally helpful during the guided project. They are decently qualified (PhDs with work experience) and do answer your questions. (Audience size is typically ~ 30/session)
- Office hours are pretty good, where you have an instructor going through the assignment and other conceptual doubts. (Audience size is typically ~14/session)
- Support hours are fantastic, these are additional hours by an instructor (mostly previous Lambda school students) who help. (Audience size is typically ~3/session). This is really helpful if you are very new to programming (meaning you had no prior experience and really want help)
It is definitely a reputed course, does it compare to a college experience? No. But who cares? But in this day and age, a college education is heavily overrated, in general colleges are not optimized for your success (in this case placement). Once you are placed how do you compare with a college graduate? Well, I don’t think the employer cares. What they care if you can write code. Period. After that, it is up to you. The gap between industry skills to college curriculum is huge. In the long run, $15,000 is a relatively cheap price to pay if you are determined, hard-working, and willing to rise through the corporate ladder. And remember the payment plan is amortized (i.e. $1250/month)
(Lambda Affiliate link)
(Springboard Affiliate link)
They have three tracks (bootcamps)
a) Data Science Prep Course ($490)
b) The Data Science
c) Data Analytics
d) Data Engineering
e) Machine Learning
6 months, Online, Live 1:1 Mentorship
1. Unlimited 1:1 mentor support
2. Career Support or money guarantee (if not placed within 6 months of graduation)
It is really important that you have a strategy to atleast be willing to live and work in one of the elevn US metro areas, namely Atlanta, Austin, Boston, Chicago, Houston, Los Angeles, New York City, San Diego, San Francisco Bay Area, Seattle, or Washington D.C.
Total 2300+ students have enrolled in the Data Science Career track.
a) Upfront: Tuition is $8940. (Pay upfront you get a 16% discount). Or pay in 6 months.
b) Deferred tuition: $12500 (Sounds incredibly similar to an ISA)
Career Track Plus
a) Upfront: $10,000 (for the entire 6 months)
Both Data Science, Machine Learning & Data Engineering cost $8940, while Data Analytics costs $6600. It might be worthwhile to know that the data analytics Bootcamp is in partnership with Microsoft
Thinkful, General Assembly, Insight, Udacity, Coursera
Practicum by Yandex
The introductory course is free
$4000 if paid upfront (otheriwse $500/month)
SwitchUp has a rating of 4.91/5 (75 reviews)
I used to teach at Great Learning (mostly for the in-person classes) and really loved the experience! The infrastructure is off top quality, the faculty that they hire is top notch and they really are committed to the students learning & development. The fees are definitely on the higher side (but it is worth it).
One con that I found is that the faculty that develop the slides (lecture) is often different from the faculty that develops the labs, & often for programming-related topics you need a sense of smooth transitioning.
This is a bootcamp that I went to for my first Machine Learning in 2017! I absolutely love this experience, it was for 6 months, intense! All the faculty is PhD (which is terrific as you know you are in the best hands). However, a PhD is not a necessary & sufficient condition to teach really well. Again, the fees was (still is) I think on the higher side but well worth it. The founders are incredibly passionate, strict, overall well worth the cost. They have an entrance test, and in the recent pas they have partnered with tons of university programs / MBA & PhD schools. That is an interesting model
I’ve heard good things about this program.
Learning data science is easy and you can learn it online. There really is no need to attend offline classes for data science (the same can be extrapolated to Artificial Intelligence as well). With our programs such as the Pixeltests Machine Learning program, you can get high-quality learning materials online and interact with other students online.
The best part of Pixeltests Machine Learning program is that it is priced at a very affordable cost. In our Pixeltests Machine Learning program, we provide real-world datasets. A large number of students have already completed the program and have secured lucrative jobs.
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