[HN Gopher] Launch HN: Turing College (YC W21) - Online data sci...
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Launch HN: Turing College (YC W21) - Online data science school
My name is Lukas. My co-founders (Benas and Tomas) and I are
building Turing College (https://www.turingcollege.com), a career
school that ensures that students are work-ready on day one of
their new position. We're currently focusing on data science
skills. When the three of us entered university, we were taken
back by the outdated teaching methods. We still smile when we
remember learning Excel via a whiteboard! While studying, we were
also running an IT and education consulting business that had an
accounting return rate (ARR) of $0.6M and was expanding fast. This
quickly taught us that the way developers are educated is not
aligned with the hiring and onboarding processes of the tech
companies looking to hire them. We saw this issue from both sides
of the hiring process. As students, we were learning subjects that
didn't prepare us practically to deliver results for companies from
day one. As employers, we were frustrated when hiring students
based only on their educational credentials, as these weren't a
good guide to future performance. So, we decided to organize a non-
profit data analysis bootcamp, where the curriculum was
supplemented with hiring partners' projects. First batches were
oversubscribed and we were nudged to build a school, which would
create specialized data science courses. Our programs are self-
paced, so we're not a bootcamp in the sense of forcing more and
more information on people each day, whether or not they have
digested the previous material. Completing a course with us usually
takes 9-12 months, but students can progress as fast as they like,
and some experienced software engineers have completed 1,000 hours
of coursework in 6 months. Conversely, students who are
transitioning to data science from other fields, and lack
fundamentals in maths or statistics, can go slowly and build solid
foundations in these areas. Students choose between several data
science specialisations, including data analysis, requiring a solid
understanding of statistics and mathematics and excellent data
wrangling skills so that data analysts feel comfortable importing,
cleaning, and manipulating data; and machine learning engineering,
focused on building machine learning models that solve business
challenges. Our curriculums are co-created with tech companies who
we partner with, who tell us specifically what they are looking for
in new hires. Since we started 6 months ago, we have had 17
companies contribute to our learning concept, including Moody's and
NordVPN. We teach current tech stacks and use specific problems
companies have worked on as the basis for projects that students
work to solve. These later turn into project portfolios that help
them get hired. Each student also gets regular industry
professionals guidance from our staff and hired Senior Team Leads,
working professionals in the data science field. They perform
1-on-1s, standups, do mock-up interviews, and more. These
professionals are paid consultants who joined us from Waymo, Unity,
and more. One student writes: "I studied in university, and at
other coding schools, but Turing College is just something totally
different. The best part is the ratio of personal tutoring hours we
get - it is 10x more than in the places I have tried before!" We
use standups and 1-on-1s with senior leads, and students get a
weekly minimum of 3 hours of personal consultation with their
leading peers and/or senior staff. Students also get feedback,
motivation and encouragement from their classmates. We have a
diverse community, including fresh graduates in STEM subjects
looking to specialise, right through to software engineers who want
to enrich their data knowledge. This diversity enables mutual
support. Those with backgrounds in maths and statistics can help
those with pure coding background, and those with experience in
business can support with soft skills. It's a collaborative,
community-oriented approach that we support and encourage through
regular live and online meetups and events. Students can track
their performance via a personalized online learning platform. It
unifies everything students need for work-like learning in one
place: projects, standups, sprints, code reviews, etc. Upon
graduation, such performance data is compiled into personalized
reports for the students to show to prospective employers and get
hired. Crucially, these reports focus not only on hard skills but
also on developing soft skills. Our hiring partners consistently
tell us that 60% of their decision-making when hiring a junior role
is based on a candidate's soft skills. Our personal development
program focuses on students' time management and growth mindset,
communication, and other interpersonal skills. Six workshops
elevate our students' soft skills awareness of each of these
different skills. Then their progress is tracked throughout the
course by having our students fill research-based self-reflection
questionnaires and during 1-on-1 meetings with mentors and feedback
sessions with staff and STLs. We make money by charging students
tuition fees. In terms of tuition fees, our goal is to take the
most flexible approach possible. Students can pay in one up-front
payment, make monthly installments, or defer payment until they are
working via an Income Share Agreement (ISA). We don't have a
preference between any of these choices, but rather work with each
student to figure out which is the best one for them. We're
looking forward to your feedback as we are really aiming to make
learning and hiring as integrated and as least biased as possible.
Author : kaminskis
Score : 68 points
Date : 2021-06-30 08:50 UTC (14 hours ago)
| master_yoda_1 wrote:
| My dear friend first tell me with bunch of jokers as instructor
| how you are going to teach data science to student. How these
| jokers are allowed to teach data science without any credentials
| atlasunshrugged wrote:
| Hey Lukas (and Benas and Tomas) congratulations on the launch!
| Always cool to see stuff happening in this space - from your
| comment it seems self paced but the website shows a cohort
| starting soon. How does that work exactly? For pricing, it looks
| like it's 9,000 euro total (with an ISA) or 5k upfront, is that
| right and are ISAs available globally or just in Europe)? How are
| you coming in so much cheaper than lambda school? Will you ever
| sell the ISAs?
| kaminskis wrote:
| Hey, ISAs are only possible for EU citizens for now. We're
| cheaper than Lambda school because we have optimized-focused
| learning platform & education processes. With that we can have
| 70% less staff to deliver the same and even higher education
| quality. We don't have plans to sell ISAs.
| atlasunshrugged wrote:
| Got it, very cool! For any students that want to freelance
| after they graduate, feel free to have them ping me,
| joel@tribe.ai (or apply directly on the site). We mainly use
| more experienced folks but I'm sure there are some projects
| where an enthusiastic new data scientist would be useful
|
| Edit: I'm also really glad you're not selling ISAs. To me the
| direct connection/ownership of the debt is what really aligns
| the parties, not the ISA itself. Once it's sold off to a
| third party debt collection agency of course there is still
| some alignment but I think the connection gets fuzzier.
| kaminskis wrote:
| Sounds amazing! Thanks, we will share this with our
| students.
| bradam wrote:
| YC recently invested in another European-based AI/data science
| online school, Strive School [0]. What are your main
| differentiators compared to them?
|
| edit: Also, can you elaborate on this: "We're cheaper than Lambda
| school because we have optimized-focused learning platform &
| education processes. With that we can have 70% less staff to
| deliver the same and even higher education quality"?
|
| Just want to understand your value propositon better as I am
| seriously considering to attend a bootcamp like yours.
|
| [0]: https://strive.school
| kaminskis wrote:
| Hi, thanks, great questions! We give a lot more flexibility
| compared to the Strive School. There are no lectures or
| schedules at Turing College, and you can progress at your speed
| by unlocking each new part of the course on our digital
| learning platform. So we target a wider audience of people from
| software engineers who want to upskill (this isn't the case for
| Strive school as they don't provide such flexibility) and
| people who requalify to data science.
|
| Also, our curriculum is co-created with tech companies we
| partner with as our Hiring Partners (we have 17 partners now).
| So, we know what those companies are looking for in new hires,
| and we adapt our curriculum accordingly; we also have their
| commitment to hiring our grads with our job placement program.
| Strive school doesn't do that.
|
| If I understand correctly, Strive School curriculum is mostly
| presented in video recordings. With us, you'll be a part of our
| tight-knit community of peers and industry professionals,
| interacting daily via online calls or discord chats and working
| on real-world projects that our Hiring Partners are now
| solving.
|
| As for the "70% less staff to deliver the same and even higher
| education quality ", this is enabled by letting students assess
| each other's work with the supervision of Senior Data
| Scientists. It means that we don't need senior staff for every
| project assessment but only for crucial ones. So by having the
| platform that organizes assessments in that way, we ensure the
| quality and the need of less senior staff. We can track how
| students are assessing each other, and they are doing that
| objectively. With our learning platform, which follows that we
| can react to any cheating situation instantly.
| seanalexander wrote:
| It appears as though they are not hiring teachers. Not sure why
| they're eager to find students but not looking for talent to
| teach those students.
| tmoska wrote:
| We are hiring industry experts (we call them Senior Team Leads)
| to consult and help our students. They are not teachers in a
| traditional sense, since they are not running daily classes.
| You can read more about their role in our blog [1]. We're
| constantly looking for more mentors and if you know anyone
| who'd be interested - we would be happy to talk to them!
|
| [1] https://blog.turingcollege.com/senior-team-leads-at-
| turing-c...
| karolisram wrote:
| Education is long overdue for disruption, so whatever moves the
| needle even a little is huge in my eyes. And it's the first
| Lithuanian start-up that I know of to be a part of YC, congrats,
| this is a great win!
| kaminskis wrote:
| Thank you, Karolis!
| truth_ wrote:
| In my opinion, education cannot be meaningfully disrupted
| untill employers and people deciding the entry on higher
| education validates the disruption.
|
| Disruption happens by innovative, open minded people. But
| boardrooms of most companies and admission committees of unis
| are filled with _legacy_ people most of whom are there because
| their parents put them there. For academia, there are only
| people who took a traditional path for education. And they only
| value who are trying to get there by those paths only.
|
| First, higher education sector and industries need to validate
| the the disruption for that disruption to be really meaningful.
| chevill wrote:
| I've heard that those who seek to pay for an education are
| usually unfit to evaluate its quality before they enter into an
| agreement. Might have been a paraphrase of a Socrates quote IIRC.
| I have basic coding skills and do DFIR professionally but I don't
| know much about data science/ML and I don't have experience with
| a lot of the math involved. So not being equipped to evaluate the
| quality of the instructors due to my own ignorance, I had a
| question:
|
| The website states that 70% of the instructors are industry
| experts. Are any of them known to the Data Science community
| outside of being backed by Ycombinator?
| tmoska wrote:
| Thanks for your question!
|
| A good example is Dovydas Ceilutka, our Lead of Data Science,
| next to being ML team lead at Vinted (2nd hand clothing
| marketplace, valued at $4.5b), he is the President of the
| Artificial Intelligence Association of Lithuania and a founder
| of Tribe of AI, artificial intelligence learning community in
| Lithuania.
|
| While Dovydas is well respected in the Baltics, we are in the
| progress of bringing more Data Science industry experts from
| global markets.
|
| Another way we are making sure our quality is great, is by
| working closely with companies (Hiring Partners) by co-creating
| and integrating their projects into our curriculum. This
| assures that whatever projects our learners are working on are
| relevant to the market & companies they might eventually work
| at.
| CommunityPoster wrote:
| Great project, I hope that you'll be successful. I'm pleased to
| see an european startup in the field. Do you happen by any chance
| to accept cryptocurrencies for the upfront payment?
| kaminskis wrote:
| I'm sure we could accept crypto as upfront payment.
| mywittyname wrote:
| Does Turing College actually offer a degree?
|
| Knowledge is important, but an actual degree is still a major
| consideration, since it does still determine pay bands and such
| at major companies.
| kaminskis wrote:
| We don't provide a university degree as becoming a university
| will strictly limit our pedagogical approach. Our credibility
| builds with time as more companies hire our students.
| artembugara wrote:
| Nice, thank you for making education an affordable option for
| people who don't have money for colleges.
|
| My piece of a feedback. "Good data scientists are in huge demand"
| -- that's what everyone says. But I believe "good data
| scientists" are usually PhDs with a few years of experience.
|
| I don't want to say your program isn't good enough. I think if
| you can educate someone to have an entry Data Science job in 6
| months then it's a great success. By "entry DS job" I mean a real
| DS job: not Excel munging.
|
| Your 6 months course seems like a bit of everything: which is
| fine because it's an entry course. But it's not much different
| from any other entry-level course. What differs you?
| CosineTangent wrote:
| To add to this: for someone who has never done any data
| science, how would you go from zero knowledge to machine
| learning, for instance?
|
| This would require learning calculus, then statistics &
| probability, then linear regressions & generalized linear
| models, then machine learning(NLP, machine vision and/or AI).
| I'm not sure how someone can learn all of that in one year let
| alone 6 months with no prior experience in the field.
|
| I can sort of see it being done but it would have to be very
| superficial knowledge which is sort of useless when your trying
| to recreate some paper that uses advanced stats and math. You
| could maybe recreate the paper but you would essentially being
| shooting in the dark and you wouldn't really know the
| limitations of the model in any meaningful way.
|
| Im curious to know how they will address this?
|
| I don't think you need a PhD in statistics or machine learning
| to be a good data scientist, but I'm just having a hard time
| believing all the skills can be learned in less than one year
| without any experience.
| artembugara wrote:
| Agree. Market is overloaded with Data Scientists with a 6-12
| months courses.
| kaminskis wrote:
| Thanks for questions. Almost all of our students have prior
| knowledge of university-level mathematics or did some coding,
| data courses on the internet. Of course, we have several
| students without such knowledge; nevertheless, they are fast
| learners. We test this in our admissions and in the very
| first month of learning in Turing College. If students are
| performing poorly, we terminate their contracts. In this way,
| we keep only motivated and determined students in Turing
| College and ensure that they would get a decent market
| salary. From the employers' perspective - just a few entry
| data science positions require independently "recreate some
| paper that uses advanced stats." Our students become a part
| of established data science teams, where some do more data
| analysis while others data engineering. As well as our base
| curriculum is more generic, our students get concrete, hands-
| on skills relevant specifically for hiring partners in
| specialization modules, which companies themselves create.
| When students finish these modules, they have a strong
| understanding of the company's business problem and tech
| stack, which is a competitive advantage over other
| candidates.
|
| The thing with data science that it is a pretty new field,
| and data scientist tasks differ from company to company.
| Partnerships with companies help us understand the maturity
| of data science in every company and prepare students
| accordingly.
| runawaybottle wrote:
| _If students are performing poorly, we terminate their
| contracts._
|
| What do you mean by this exactly? You are school, right?
| It's not possible you are not teaching them right? Should a
| person not have the right to fail the course from start to
| finish?
| tmoska wrote:
| Everyone surely has the right to fail projects & work on
| their improvements - that's a large part of learning. To
| clarify Lukas' point, we are constantly in contact with
| every single of our students and are making sure that
| Turing College is bringing value to them. In cases when
| students are progressing extremely slowly because of some
| factors, we have a process through which we inform
| students of our concerns and start having more 1on1s to
| help & support them.
|
| The reason we are doing this is that at a certain point
| knowledge starts to "fade away" and even if you are in
| the middle of a course, you might start forgetting things
| you learned at the start of it. That said, self-paced
| learning is unfortunately not something that works for
| everybody. Our students get to try it out in our
| admissions process & demo month[1] to cancel free of
| charge before they commit.
|
| [1] https://www.turingcollege.com/faq/what-is-the-demo-
| period-an...
| burnished wrote:
| I think this is a valid line of questioning but
| personally I'm not sure everyone should "have the right
| to fail the course from start to finish" on the basis
| that it can be a severe drain on resources and perhaps
| even unfair to the person falling behind. If the work is
| highly collaborative then the person who fell behind
| becomes a burden for their peers. If that is not a
| concern you will still get people that either squeak
| through without flourishing (reducing the overall quality
| of your graduates), or people that realistically did not
| have a chance from the outset that then get denied at the
| finish line.
|
| For the purpose of trying to determine what is or is not
| fair I don't think it matters whose fault this is (a
| failure of the school's pedagogy or of the student's
| ability to keep up) because I think allowing the failure
| state to continue is fundamentally unfair.
| ampdepolymerase wrote:
| The prereqs for ML are the same for most STEM courses.
| Despite the popularity of CS, there are plenty of graduates
| in legacy engineering fields like mechanical and electrical
| who are more than equipped to be on boarded quickly via a
| bootcamp model. They have the knowledge (and usually know
| their way around basic Python and MATLAB) but lacks the real
| world software engineering experience and a developer's
| mindset.
| snicker7 wrote:
| I love to how you refer to electrical and mechanical
| engineering as "legacy".
| onion2k wrote:
| _But I believe "good data scientists" are usually PhDs with a
| few years of experience._
|
| This is the same argument that says only people with CS degrees
| can be good software engineers. That is provably wrong because
| there are good software engineers who don't have CS degrees.
| Good data scientists are just people who can do data science
| well. That's the _only_ valid measure. Having a PhD and some
| years of experience increases the likelihood of that being the
| case but having those things doesn 't automatically mean
| someone is good, and not having them doesn't automatically mean
| someone is bad.
| kaminskis wrote:
| Several things make us different:
|
| 1) Our program is self-paced, while almost all bootcamps have a
| strict learning schedule. We ensure accountability through
| daily meetups, 1on1, and project assessments. Turing College
| suits people, who work full-time and want to upskill part-time
| by flexible schedule. As we have platform, which organizes all
| the learning activities for students, project-assessments
| happen from Monday-Sunday from early morning to late evening
| without our operational staff involvement.
|
| 2) Students spend 1/3 of their learning time on hiring
| partners' projects. Companies create projects that reflect
| their business problem and tech stack. Thus, our students are
| more ready to deliver from day one than other bootcamp alumni.
|
| 3) Students learn everything through practice. I know this
| could sound cliche as many bootcamps claim to do that, but in
| reality, it is just happening on paper. We have a custom
| platform that organizes curriculum into data science projects,
| which each of them should be assessed by a minimum of three
| people. To finish Turing College, students need to complete 20
| projects that should be peer-reviewed by Senior Data Scientists
| and peers. Through this process, students get a lot of feedback
| about their learning and overall performance. They also need to
| assess at least 20 projects to finish the course - by this,
| they are pushed to learn to examine other's work, which is
| crucial in every technical position.
|
| 4) Students have personal development programs to improve their
| habits, communication skills, critical thinking, etc. Many
| employers' problems are related to the human factor, so we
| focus on shaping essential soft-skills parts.
| educat3 wrote:
| I'm very intrigued by a lot of the new education opportunities
| coming out of YC. Lambda have highlighted a few concerns with
| this model, which I think you mostly address with selective
| admission, course specialism and experience, that said I have a
| few (Lambda inspired) questions:
|
| 1. The total cost (5k direct[1], 9k ISA) is significantly cheaper
| than Lambda: do you see that as a reflection on the cost
| sensitivity of the European market or is there a reason your
| model allows for lower-cost execution?
|
| 2. The ISA model gives the school a vested interest in the career
| outcomes of students, but Lambda has highlighted that ISAs can
| become a debt product that is resold: do you see that model (of
| reselling ISAs) as part of Turing College's future?
|
| 3. Lambda has had problems with new courses being unable to
| deliver on the promised quality: how do you see the next few
| years of growth for Turing, do you expect to introduce new
| courses based on demand or do you expect to build out new
| curriculums (and test with whole cohorts) before introducing
| them?
|
| 4. What's the relationship between supervisors and Turing? The
| team page notes that these people are part-time with Turing: how
| do you ensure that they're able to deliver the valuable
| mentorship required by students? Are they volunteering? Paid per
| hour? How does their mentorship accommodate students that require
| more support than average? Does their commitment to Turing come
| before their work, with their employers supporting?
|
| Very promising proposition, team etc: very interested to hear
| answers to the above to better understand how you are approaching
| the more challenging aspects.
|
| [1] I'm an employed Software Engineer but at that price it's very
| tempting to enroll to build out my data science skills.
| hintymad wrote:
| I feel that the challenge of Lambda school, as well as other
| vocational schools, is that their courses are too specific for
| too short a period with too easy assignments. Take this
| curriculum for example: https://lambdaschool.com/courses/data-
| science#curriculum. Stats fundamentals: 4 weeks. Predictive
| modeling: 4 weeks. Etc etc. I mean, really, 4 weeks for stats?
| Will the students have enough time to learn fundamentals on
| counting with such short time?Will they truly learn what a
| random variable is and why that matters? Will they learn what
| joint probability distribution is, what test of hypothesis is,
| and what pdf, cdf, and pmf are? Will they learn what an
| unbiased estimation is? All these concepts do not even scratch
| the surface of real data science work. Unfortunately one will
| not be able advance further without firmly grasping these
| concepts. And I'm just talking about problems at undergraduate-
| level. In addition, can we realistically ask the students to
| work on moderately challenging assignments given such a short
| time? If they can't, why would I, as a hiring manager, risk my
| team to hire a graduate from such schools? One may argue that a
| motivated and smart student can overcome such obstacles and get
| her foot in the door by attending such schools. But then the
| challenge is flipped: not many such students need to attend
| such schools.
| catwind7 wrote:
| > One may argue that a motivated and smart student can
| overcome such obstacles and get her foot in the door by
| attending such schools. But then the challenge is flipped:
| not many such students need to attend such schools.
|
| i guess it question is is there enough such students who can
| overcome these obstacles who are also willing to fork over X
| tuition? they may not need it per-se, but I think you may be
| discounting the value of the pre-existing networking leverage
| these schools have over individuals that may have no network
| in data science related work
| tmoska wrote:
| Great questions! I'll go through them one by one:
|
| 1. You are correct to say that our pricing reflects the
| European market and is naturally different from schools in
| other markets. In addition to that, we are a self-paced school
| and have no actual classes happening (work-like learning). Our
| students get projects via our platform, attend daily standups
| and receive (from mentors & peers) & do (to peers) code
| reviews. This means we have no full-time teaching staff, and
| that's a huge cost-saver. Instead, we spend more effort on our
| underlying tech & mentors, which results in a lower variable
| cost per student. Important to note that even though there are
| no classes, our students still receive a lot of contact hours
| with industry experts through code reviews, help sessions,
| standups, etc. These hours are focused on helping our students
| (2-way), not teaching them (1-way) - just like you would have
| it in any workplace.
|
| 2. We don't have plans to resell ISAs. We see ways to be a
| successful school without taking this path.
|
| 3. We believe in being focused, and Data Science[1] will
| continue to be our main focus. We do not plan to start any
| courses in other fields.
|
| 4. Our mentors (Senior Team Leads) team is hired by Turing
| College and is paid by the hour. We do have agreements with
| each of them about their weekly involvement and each of them is
| managing their time themselves. Because of our education model,
| STLs don't have to always be available at specific hours. They
| mark themselves available at specific hours and we have ways to
| assure consistent availability coverage for help & code
| reviews. Because of this, our students can get code reviews any
| time of the week, including weekends. As for students who
| require more attention, that's completely fine, and they
| receive help from our staff, mentors, and other peers.
|
| [1] https://blog.turingcollege.com/data-science-job-roles-
| explai...
| educat3 wrote:
| Thank you very much for the comprehensive answers, very
| insightful and reassuring about the future of Turing.
| Hopefully I'll see this all in practice in September :-)
| mpva wrote:
| I'm confused.
|
| The code you have on one of the quiz questions is:
|
| ----------------
|
| a = 1 b = 2 c = 3
|
| def calculator(a,b,c): b = a - c a = 2 return a+b
|
| x = calculator(c,b,a) print(x)
|
| ----------------
|
| This returns 4. But the only options you have are:
|
| A. no output B. 0 C. 3
| mintone wrote:
| The iframe that the form is in is too small. 4 is there, you
| just need to scroll
| Alisa_honolulu wrote:
| Yep, make sure to scroll down to pick the right answer; which
| is 4.
| alexgmcm wrote:
| 4 was an option for me. Perhaps you had to scroll to see it.
| sonograph wrote:
| > 17 tech companies contribute to our education model.
|
| Pedagogy isn't something that tech companies are particularly
| known for, nor hire many experts of.
| tmoska wrote:
| That's completely true. Companies contribute to our curriculum
| by co-creating projects. We work together with them to create
| these projects and are heavily involved in this process to
| assure quality.
|
| Reasons we have this are: 1. For students it's a great way to
| see what tech stack is the company using and what problems they
| are solving.
|
| 2. For companies, each coming-in student has a "technical
| interview" already completed and a lot more context about the
| company.
| shayankh wrote:
| how to apply as a teacher?
| Cd00d wrote:
| Aside: at my company ARR stands for Annually Recurring Revenue
| (and is explicitly defined at _every_ town hall), rather than
| "accounting return rate".
|
| Is one of these wrong, or is it just a case of more than one
| meaning for an abbreviation?
| kaminskis wrote:
| It should be Annually Recurring Revenue, somehow the different
| definition was pasted here. Thanks for making a remark.
| verdverm wrote:
| Thought this was related to https://turing.edu/ (a non-profit)
| before digging deeper to see they are using the same name (FYI to
| OP).
| kaminskis wrote:
| We aren't related with this Turing.edu. We are aware of them
| but we don't have any legal problems regarding trademarks as
| our brand is protected in Europe.
| verdverm wrote:
| I noticed that. They have an even smaller target audience
| being an in person bootcamp.
| booleandilemma wrote:
| Have the hype and bootcamps moved on from programming to data
| science?
|
| Can we have a normal profession once again?
|
| Are the frauds all going to start calling themselves data
| scientists now?
|
| I just went through 5 days of interviews for a single company.
| elnatro wrote:
| Congrats! The pay scheme seems like a good way to get some trust
| from the clients.
|
| However, I'd like to know if a similar way but being a part-
| time/flexible student is available?
| kaminskis wrote:
| Yes it is. We look to everyone's case individually and it's
| possible to be a part-time student having ISA.
| edent wrote:
| What relationship do you have with the estate of Alan Turing?
| slownews45 wrote:
| For folks looking for a shorter / cheaper crash course I've seen
| this one pop up that seems connected to a practical environment
| to use long term.
|
| https://developers.google.com/machine-learning/crash-course/
|
| I'm tempted to try this to add SOME data analysis skills to my
| existing skills.
| [deleted]
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