Thanks for watching everyone! It is an uphill battle, but I still believe that it is possible to make it as a new entrant into this profession! Also, sorry for the self plug, but if you're looking to stay up to date with what I'm reading, learning, etc. I would love it if you signed up for my newsletter! www.kennethjee.com/newsletter
Becoming a software engineer is also very difficult with out a CS degree. You need to learn coding in few languages, oop, design patterns, system design, web tech, and algorithms and data structures. I also find that algorithm & system design interviews are difficult than data science coding interviews. I am too struggling with keeping up with required skills for DS. The list demanded by employers are getting longer everyday. I think best thing to do is first become a data analyst, it is just like become a front-end developer or programmer in tech. Then gradually build your skills. This way you will also build your network with analyst and data scientist. If you try to learn everything and then attempt to be a data scientist, you will suffer and probably even given up.
It's can very well be a "who you know" industry as well. (As many are) A friend of mine got a job as a data scientist because a company didn't really know what a data scientist is capable of, but through conversations with someone at the company, explaining what he's learning and able to do they brought him in on a 6 month contract to test the waters. His work resulted in the company finding inefficiencies in their supply chain that went completely unnoticed for over a decade. Needless to say they offered a full time position and expanded their data analytics/data science department.
I have graduated in civil engineering.... But I wanted to be a data scientist... I have picked up a online course from coursera powered by IBM.... & I do follow you as well so that I can get more knowledge.... One day I will be a successful data scientist... ❤️
I just graduated from Manufacturing Engineering and currently starting out as a data analyst while self studying and taking online courses to be ready to transition to data science one day. We got this!
and then after you became a data scientist, you will realize that after all, its just a statistics with extra software engineering skills. Too many people get stucked in a cool complex algorithm trap while the most important thing in becoming a data scientist (unless you work in a really specific field like NLP & Computer Vision), is to have a solid statistics base
Thank you for the great video as always Ken. The grit aspect towards the end really speaks to me as someone trying to enter into the field. I remembered when I first started out going into this field my first year at UC Davis, I felt a major hit of imposter syndrome. It all really started out with when I interviewed for a Data Science project for the Data Science club at UC Davis. The president at the time (who interviewed me) asked questions about my project experience, interest in sports (this was a sports analytics project that required computer vision to analyze the movements of players), last book I read, project experience, and my SAT math score. As I answered those questions, he didn't like many answers to any of them (never had projects because I just learned how to code from my Introductory Python course I took the quarter before the interview, not into sports, stupidly said the last book I read was "To Kill a Mockingbird" even though it was a book about Robert Kennedy (I was kind of nervous here), and I scored in the 600 range for math) and proceeded to say this, "Look Jeffrey, I know there's way smarter people than you. Tell me, what makes you stand out?" My response was, "Uh... I'm willing to work," and he said, "*sigh* Everyone's willing to work." I basically failed the interview and he basically implied that this field isn't for me (to add insult to injury, I saw someone do better than me at the interview right after I finished). Not only that, some people thought that I would end up at McDonald's after I graduated. To compensate, I did side projects throughout sophomore year, got accepted into Facebook's Data Science mentorship called the Facebook Data Challenge 2020, secured a summer internship as a Data Analyst at the Federal Reserve Bank of San Francisco, got accepted into the MURPPS Research Program at UC Davis, and I'm on my way to prepare for an interview for a Bioinformatics Research Position in the Molecular and Cell Biology department at UC Davis to use machine learning models to predict the structure of DNA/RNA to determine how this can lead toward genetic diseases. I'm glad that having developed a sense of grit throughout the years has been so far useful for not only proving people wrong, but also giving me great opportunities.
“Data Science is the Frankentein of Computer Science with Statistics and Business knowledge”-How a quote can be funny and meaningful at the same time..haha
I honestly came here because I just started learning about data science and was considering it as a career opportunity, and this video was great for helping me not only feel informed on how much education is needed but also that the market is SATURATED. I'm leaving a saturated job market, so that's really important to me! Thank you!!!
I agree. I just graduated with a BS in Data Analytics- I came from the background of zero programming knowledge. The beginning part of understanding the concept, syntax of these programs were extremely difficult and questioned myself a few times. But through many hours of study and self motivation, I began getting a comfortable understanding to the logic and usage of these different tools. I now feel confident using and explaining data science, and now thinking of pursuing my graduate degree in DS. I want to tell anyone reading this. Keep pushing and pushing, you to can learn data analytics, but like ken said, you have to have the grit and willingness to push through adversity and ambiguity. I hope I am able to land a job soon as a data analyst. Good luck to all!
I think #3 is by far the most important. It's pretty easy to get sucked in because everybody else is. Maybe this is not for you though and that's okay! You're not a failure for realizing that and going after something else.
3:12 Yes, love for the process is definitely a good reason to become a data scientist. This reminded me of Michael Jordan’s contract including a clause on “For the love of the game” . I am with you on Grit and Persistence as well as patience as the large skill sets that would shape us to become the unique data scientist we would become takes time, care and nurture. As Rome is not built in a day, becoming a data scientist or being a data scientist can take a lifetime to attain or maintain. Thanks Ken for this thought-proving video!
Love this comment data professor! One thing I didn't mention related to passion and "a reason for doing it" friends with similar interests help to motivate as well. You've definitely been one of those for me on this RU-vid journey!
@@KenJee_ds Wow, very honored and likewise, I am always inspired by your content and your innovation in this space. I definitely agree with you on this, the journey is very much enjoyable when you have friends with you. Thanks!
I love to learn and my friends say I have a thirst for knowledge. Some odd reason lol I kinda like the data cleaning aspect. Honestly I want to learn data science to align with my life purpose
That is awesome! Honestly, if you love the cleaning process, you may want to first look into data engineering. That is the fastest growing part of the data science domain and a lot of opportunity there!
In a nutshell, DS is hard to learn and put in practice because it requires a lot of passion to learn a lot of topics from different fields, and obviously there's is not a roadmap to learn all these skills. Imagine that you are living as an architect in the earlies of the industrial revolution, then suddenly there's a boom for mechanical engineering with not structure at all to learn all the stuff. You'll have to learn by yourself physics, math, thermodynamics, etc. This is how DS is, is a new field and a lot of information to drive someone crazy.
I suppose the first challenge is the most obvious especially in a bank I work for. All dudes are at least holders of Masters in Maths or CS etc. In my current position I work within members of this team and they're all very good in DS.
Hey, It is good to know the challenges you will face in achieving a particular thing. Thanks for that... 66daysofdata data helping me to nurture the good habit of data science learning. I will try my best to achieve my goal...
My personal advice is to start as a Data Analyst (or Business Analyst), study on your free time and kick ass on your job. If you're open to your boss and he/she likes you, it will be much easier to make an internal transition to ds inside the company you already work for. It's not still not easy tho.. good luck!
i also climbed the analyst stack: analyst -> statistician -> data science even when u get to data scientist, you'll want to be a ML engineer, or a cloud engineer supporting ai applications their is no bottom to how deep technical skills go
True indeed, I have worked as a data scientist for 2 years shifted my focus from data engineering to data science and after 2.5 years took a complete U-TURN and currently settled with ML/Data engineer. One thing I enjoyed working with DS is to get a complete understanding of maths behind numerical computing library such as TensorFlow, which was quite rewarding for me. Although during the journey, I realized that I always want to be an engineer and moreover there is more opportunity as an Engineer rather than being a data scientist.
Great video mate. I am currently completing a MSc in Data science (4 courses done). While I am loving the learning process and fascinated by the field, I have no current plans to have a career in Data science. I get way too caught up when working on a project (especially when debugging code) that other aspects of my life and frankly sanity, suffer. So I can't imagine doing that for a living, as I will never disconnect enough from work.
Thanks for watching Kenny! I think that having the data science skillset can make you more effective in many other types of work! I think it is awesome that you are learning about it though!
I’m a seasoned data analyst and can say the following. The big data domain, so that’s data science (aka machine learning), data analytics and business intelligence, are tech fields, but not colourful ones. The focus is business strategy from a data-driven perspective. You do not deliver products as you will not be building or designing applications. You deliver insights, and in time this will have an impact on the business. So no fast/direct impact. Very high-level. You need to like thinking long-term about the business. So no colour, no app building, no designing. It’s all about strategy. You are not a developer; you are a strategist. So if you see yourself doing that, go for it. If you see yourself building or designing, don’t go for it and go for development/designing jobs. Now, there actually is a development type of job in the big data domain: data engineering. But that’s boring and really the data preparation work that nobody wants to do. They just prepare the data for the analysts to analyse. That’s it. I’m sorry for all the data engineers reading this, but it’s the truth and you know it. But hey, if you have a passion for that, go for it what can I say. So this sums it up. Good luck 👍🏻
Thanks for the tips. I am interested in data analysis for public health care. I am a public health physician currently working in the field of HIV/AIDS. I would be delighted to get ideas on how to start a career in data analysis. I am presently learning excel but don't know the areas to focus on. I also need to join online communities of public health data analysts.
New look I see💯 I think for me it time management with college and data science and Internship going on hard to handle and also take care of my personal needs etc is hard but putting in efforts also loved your point and reality check this willl help us to make some relatistc expectations and also have backup and be ready adjust a but when time comes 💯🙌
Yes, time management can be very difficult! I will say that it is important to look at data science and learning in general as a marathon not a sprint. You can balance learning / school etc. over the long haul rather than equally right now. For example while doing your internship, you probably don't need to do as much (if any) outside data science study. I hope this helps shruti!
I will become a data scientist for sure!! With one course on Udemy I figured out to clear up my basics and going on continued with the journey for the basics. Will learn it at any cost !! ❤️❤️
Great video Ken! I feel you, I cried two days ago trying to fit data into SVM and Adaboost. The first worked, but the second still doesn't. Gotta keep on grinding, eh?!
The odds are surely stacked against me being 46 years of age and only having worked jobs that pay minimum wage or $1 above minimum wage at most, and no related job experience. Yet, I still refuse to give up on the good life even if it means settling to be a data analyst or some other computer science job like software engineering, data engineering, DBA, etc. If I want the good life, quitting is not an option.
That is the right attitude to have! It is totally ok to start with a data analyst or swe role and move into data science from there. You could look at it like a stepping stone! If I had to go back, that is likely how I would do it!
DS will probably eventually just be broken apart. Data engineers, ML engineers, DAs, etc. I like the tech side of it personally so I’m leaning more towards engineering and analysis. But that’s just my preference. It can be hard to break into “data science”. So I’d tell people to not get so hung up on the title. When I finished my internship I had an offer for a data scientist role and a data analyst role. The DA role played nearly twice as much and used much of the same tech. Keep your options open.
I agree - I think a lot of industries are generating a lot of data and to have some data analysis skills is quite valuable whatever job you have. You can then use a combination of analysis and optimisation to improve our output. At least that is what I am trying to do as a Mechanical Engineer 💪
I also agree! I think ambiguity in the positions is one of these that irks me the most. It is a vast inefficiency in the market that should eventually correct!
This is very true. I have gotten acceptance on this, as I am at the beginning of my journey. Plus, I am convinced that this is going to pay off with a Fantasy Football championship. YES!!!! TOTAL FANTASY FOOTBALL DOMINATION!!!! BWAHAHAHAHA!!!!?!
Yes, I whole heartily agree with you that education is a important requirement. I would be careful in putting "Barrier to Entry" and "Education" in the same sentence. A lack of education is a barrier to achieve one's potential. Also you need to apply what you learn and not let it perish or atrophy over time. I have copied code that I didn't fully understand and got it work. I believe that there are amatuer data scientists out there that one day could turn professional.
Brutally Honest video. Brutal but Honest. Thanks Ken for showing the reality . However I will still follow this path. When I started this journey I promised myself that I will do whatever it takes.
I think it is all what you get out of it. I would do your best to leverage the university resources (jobs, research, etc.). I would also spend as much time as you can in an internship or working on projects. These will what pay the most dividends.
Hi Rohan! Congrats on the role 😊 just uploaded a day in the life of a data scientist video - would love if you checked it out for some inspiration before you started your role :)
I just created Resume and currently preparing for Interview. And I don't have any degree. I don't have anything that is good related to Education to put on Resume. Everything relevant for Data Science I Learnt by myself. In few days I'll start applying. Don't know what will happen Since I don't have a degree
Good luck Krishna! I'm interested to hear how it goes as well. I think that you may have more success on non-traditional channels like linkedin, cold email, or with sharing any projects you work on. I hope this advice helps!
The thing is many countries like USA and Australia, don’t have protected titles for ex. Everyone calls themselves software engineer for just doing “ web development “ work”. Which is absolutely BS. Same with data scientist, many of them are actually data analyst but call themselves data scientists they are two completely different things.
Appreciate this Ken, I watched this to really test my mettle before embarking on my masters in data science and AI because it was on my recommended list. Safe to say I paid attention to the points you made but I didn’t feel disheartened at any point! Thanks for this video and pointing out the challenges faced, I think it’s very important to be aware of these challenges beforehand.
@@pravanw.5365 I am yet to start, which will be in September. In terms of balancing the two from the prelim research I’ve been doing over summer the fields are intertwined and mesh together fairly well. Maybe I would advise that starting early and really devoting yourself to the craft is the way forward, be worth it in the end.
@@Phoenix-sh8vg thanks mate for the reply.. one question if you dont mind me asking.. does your masters have the same amount of content in AI as a usual AI masters or is it less to give time for the data science part?
@@pravanw.5365 My apologies only just saw this, I believe it’s largely a splyce of the two, as I am learning modules such as data mining and I chose optional modules such as Bio optimisation which is quite AI heavy.
A classic marketing, they show you your weakness and your barrier to make sure you feel scare. Then, they sell their product or promote their youtube video to get more adsense
I think consistency is the most important thing I learned this year, with channels such as yours and with challenges such as #66daysofdata and #100DaysOfCode. Specially since my college classes are not tech related, since I study political science, but I want to incorporate data science tools into political analysis, so having a schedule of 1h of learning and coding everyday is helping so much! I might not become a data scientist per se, but I really believe that with consistency and perseverance I will be able to learn the skills by the end of the year! 😁
Really happy to hear the challenges were helpful Amanda!! I think that data literacy is going to be even more important in politics in the future. Looking forward to seeing you lead that revolution!
Great video. I've been following this channel it's been a while. I'm at a tough crossroad now. My current field is Industrial Engineering (machinery maintenance). I want to switch to Data Science so I can make use of my academic knowledge to the full (Maths and Programming), also because I think DS is more Future Proof. I couldn't reach a firm decision yet, still hesitant. People who made a career shift to DS, what are your thought on this?
Thanks for watching Anthony! I don't think you have to make a full "Jump" at any time. You can continue to aggregate the skills, do projects, etc. over time. You may find a role in the future that combines IE and data science that would be a perfect fit. I would look at it less of a crossroads and more of a slow transition gradient. I hope this helps!
I will be graduating in December (Ph.D. Chemistry). I am interested in getting into Data Science. Have you got any good starting point and tips for me? I got a bit worried watching your video there 😅
I am still at uni (bs comp sci) making a career pivot, and I must say I was hesitant to watch this video (scared the title would be true)… Anyway, I watched it. Loved it. I still love data, and learning (even though the uni mountain seems HUGE sometimes) and you didn’t scare me off. I will get there. Keep up the good work, love the videos and the newsletter!! Oh, that blooper was gold 🤣
Thanks for the video Ken. I've just started studying a data science certificate and am absolutely struggling. I'm just say "grit and determination" to myself over and over!
Hi! Would you mind sharing how you got into data science? As in what was your path to this career and what you suggest for someone still deciding where to go to college.
I made this video on the topic! ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-n3vw0M5RrPU.html&ab_channel=KenJee I also made this video for college students which I think may help! ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-xjhW1rSQeik.html&ab_channel=KenJee
I think that it the skillset for MLE is perhaps a bit more specific than that of a data scientist. It will probably start to saturate more over time, but companies are constantly scrambling to find people who have the MLE skillset these days!
I got lucky and in early since I studied stats like 15 years ago and did lots of programming projects on the side. Just sort of feel into it... These days I wouldn't aim for being a ds but instead data engineering or BI / analyst stuff. Go in through the back door
Recently finished listening to the audio book of Grit - strongly recommend this book for anyone also curious about cases demonstrating principles you can apply to measure/hone/learn about achievement via a quantitative social sciences lens.
Thanks for watching Christopher! I have a few videos like that but will try to make some more. You may enjoy these: ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE--pdXWmj9xxU.html&ab_channel=KenJee ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-Uf0dO-pgOrk.html&ab_channel=KenJee
@@KenJee_ds I love the subject a lot (all those concepts and theories) but I find it difficult while applying it- the coding part... Trying a lot but not finding the right way as far as coding is concerned, especially Python.. Suggestions please..
Data Science is advertised as statistics combined with big data. This is completely FALSE. Additional information technology training seperates a data scientist from a regular statistician. What does this mean? A statistician or a data analyst has skills that can be broadly applied - every company needs them. However, a data scientist sometimes needs to work years in a company before contributing anything.
Clearly, I am not acquiring these skills to become a data scientist; I just enjoy knowing about these topics. Plus, I have some projects to boast during dinner chats.
This video is old but Ill put my two cents, I have almost 3 years experience as a Data Scientist and even now my resume can match up perfectly to a job I know all the skills except maybe 2 or 3 because I've never done it before in my experience and I still get denied ALOT
I don't wanna become a data scientist....I don't even have anything major common with that field But this video still made me reconsider my options....it good that I remembered I ain't a data scientist before applying for a ... This video was convincing 👍😁
Hey, I have a finance and accounting background, if I learn python,R and different languages and technical things related to data science, with relevant solo and open source projects, with relevant internships, can I get a good job in the field?
Hi. I did accounting as well, I spent 1 year in EY until I found myself not really enjoying it. So I took Coursera machine learning course and join in a Kaggle beginner competition. Yet still hard to get the very first job as a data analyst. I guess that a good project experience is vital for entering the field if your background is not Data Science/Computer Science.
@@yuejiang5759 I think a commerce background can only fetch us analyst positions, because the big companies probably don't trust non-technical background candidates enough for a data scientist position
Been watching hours of your material (and Tina) because while I do know that it is not an easy field, I’ve been fascinated by it ever since I first found out about it. Data Analysis is my passion and the one thing I feel I came to the world for, and this role I feel like it’s the pinnacle of it. I will not give up.
Wow, thanks for the video, and I'm just switching over my career now and I'm really concerned, I feel old because I just a starter programmer and trying to learn data science from zero. And now I just don't know what to say, I guess I don't have any possible way to not continued to pursue this career. There is something amazing and special about this. Something from the core from the foundation that I want to learn, to know, and master. The problem is that none of us are immortals. But I will continue to persist, thanks again for sharing...
Honestly i don’t know what you are on about... Having worked as a Data Scientist for our government and for the 2nd largest bank of my country (Rabobank) i can say with confidence that a “data scientist” is just a data analist with some data engineering and statistics experience... Mabey not “easy” but far from impossible. Second point i like to point out is that you should not want to work as a data scientist the rest of your life. You get paid significantly less for your work than for example working as a financial analist or data consultant/manager.. Your career path if you want to not get scammed (at least in my country) should be something along the line of: - BSc Business Informatics or Information Science - Work 1-2 year as an IT consultant or Data Engineer - MSc in Data Science, Econometrics or Statistics/Mathematics - Work 1 year as a Data scientist at a decent company - Switch jobs and work as a Financial Analist, Data Manager or IT manager. You get paid significantly more for basically less work.. my salary went from 3400€ to about 5200€ in 1 year. Worth it people...
Thanks for sharing! My experience is only US based, so I definitely don't think my advice should be generalized to other countries. Really good to know this is different in different parts of the world!
I'm in so big of a dilemma. Problem 3 states that software engineering might be a better fit then I'll see youtubers regretting their majors the instant I search. Just give me the janitor job at google.
