LogikBot - Affordable, Real-World and Comprehensive - www.logikbot.com There are two core paths on LogikBot. One for the data analyst role and one for the machine learning engineering role. I've added the data analyst role recently because machine learning has become so difficult to break into. If you're new to IT, I'd highly recommend this path. You can be in a real-world data analsyt role in under a year if you really apply yourself. LogikBot is the most affordable and fastest way to attain this role. The platform even has an exam simulator for preparing for the exam. For the data analyst role, you take two courses then prepare for and pass exam PL-300. This exam, PL-300, is the Microsoft Certified PowerBI Data Analyst Certification. If you're in a shortcut role, then there's an entire path laid out for learning machine learning. The platform used by Uber and Microsoft. I worked at both companies. The courses are real-world and comprehensive. This is not the easy way. There is no easy way. This is one of the few platform that's offers a real-world approach to working in AI.

I saw this video. As someone who majored Statistics and Machine learning at school , I can assure you this is the most honest take on machine learning engineering ever. I have been on a job hunt for more than a year already.

this is the reddest pill about data science i've ever seen, thank you sir

This is a masterpiece. Straight to the point, confident, and most importantly helpful.

Thanks for the no BS talk. you have no idea how many people need a reality check before starting off on a huge journey such as this, myself included.

Hey Mike, you saved me two years of study with all your videos. Thank you so so much. Will sign up for your course

This is one of the best advices I´ve found on the internet, I´m pursuing a PhD in Intelligent Systems but didn't get much real world insight from professors, most of them are in Research rather than production environments. The most important real world insight was when I worked in the electrical industry and realized there is a necessity of data related roles in the industry, nonetheless didn't found where to look on how to become a Data Engineer (Most of the posts and everything is like courses of people who is not in real world applications), is it better to master python and SQL to become a data engineer rather than other languages or frameworks? Personally I really like Math and Statistics but realized that most of the tasks in PhD of writing regressors and Perceptron from scratch is not necessary for applications since there are many libraries from model teams with very efficient programming and optimization, the critical step is cleansing data and picking the correct model. Thanks for your videos, any suggest is welcome.

I watch this video like 10 times There’s a lot of insight

Thanks for the Complete and most detailed analysis i have found on youtube.

Hey my brother! So this is my goal on how to become a machine learning engineer! Im a freshman in college but imma follow your approach. Its been tough finding roles in this freshman year. I’ve been unemployed this whole year but this has been great learning experience to see how tough it is to get a part time while studying and this will grow my tenacity when searching my role in being an ml engineer

Wow... Thanks for the straight talk. I really enjoy the frankness. I will will be watching more of your vids.

Thanks a lot for bashing me with this fact, it makes me more motivated to learn

Thanks for this one. What you mention just confirms what I have learnt so far. Just for the sake of sharing, I have been a "machine learning engineer" intern at a financial institution (a microfinance more precisely) for 6 months during which I explored the task of building credig scoring model for existing customers. I have read books, papers, blogs which helped me understand the field of machine learning. During this internship, I have also made so many mistakes during the model building phases. I consider this internship as a "failure" since what I built won't surely work in production but I have learnt a tons.

I found you Data Janitor, Michael West straight from Quora. Your 30 years of experience in data speaks volumes. I have watched a number of your videos and found them well-curated, resourceful, and bare truth with no embellishments. You have no time for sideshows and theatrics. I am in my 3rd year of Bachelors in Computer Science. Is it advisable to model my career in Big Data by starting in a Data Analyst role and working upwards? According to most of your videos, one can get an entry-level data analyst job straight from a bachelor's program.I will appreciate your advice on this.

I love this guy's honesty.

Great video. I didn’t realize the data scientist role was actually a ML engineering role. I am still undecided as to where I want to take my career but I recently learned about the research side of things and was wondering which position has a bigger impact on a company, a research scientist/engineer or a ML engineer.

Thank you for making such straightforward content.

TRUTH! Great info here. I will have to check out your platform.

Love your videos, somebody who is really telling the truth and I love the phrase "the real world".

Thanks for this! Much appreciated

I really appreciate your video. It did reassure me that what I've been doing is a right bath. Also, I've noted some great information

Love this video! I just am finishing up my masters in computer science and I really want to get into ML, thank you for the advice!

Honestly I am surprised how you don't have 1 million subscribers . You really get to the important points

very good info. please keep posting.

Thanks for the video. Great info. Very honest. I have been a SQL developer, BI developer, ETL developer, performance DBA for over twenty years. Currently working as a junior Azure data engineer. BS appl math, MS data science, proficient in python. ML jobs are extremely difficult to get, even a first interview. I might go the data analyst / PBI route to become an ML engineer.

Interestingly, I suddenly came across your video just after I joined a Kaggle competition for fun. I watched quite a few of your videos and they have been helpful. Straight to the point, no background music and annoying stuffs. I have also visited your platform and will subscribe soon. As an enthusiast and beginner of the machine learning field, what would you recommend for me? I know some python programming, know some machine learning stuffs, and learning SQL inspired by your video. Have a great day!

Little harsh, but true for the most part. However, you forget to mention that with a masters or phd (mostly just phd) you can get an Applied Data scientist position, though this is not a machine learning role like you said and is harder to get. Also, these roles are really for the best of the best, so definitely not an entry level job or an easy path. If someone is looking at the MOOC content just starting out and hoping to get one of these jobs, then yeah your advice is what they need to hear.

Thank The Algorithm for reminding me that I need to move with purpose by recommending this video

The only cool eye-opening video I have seen....thank you

I am pursuing my Master's in Data-Science and I truly respect you for preaching the facts. Most of my colleagues and me(of course) believe that a Master's degree in Data-Science implies expertise in Machine Learning and to quote you, 'You are in for lot of heart ache' is putting it nicely. 😅

I feel like Vic Mackey just hit me in the face with a book of hard truths then burnt my face on the stove of reality. Thanks!

Also thank you so much for your video and guidance.

I have watched some of your videos, and I quite like you no sugarcoating approach, however as an engineering student that had taken SQL for two years, I don't understand your point about SQL, I have never actually worked with it in any real world project, but it seems pretty easy and I can't wrap my head around the fact that you think that this takes two years of experience to be decent enough to apply for a machine learning job. I wish you can elaborate more on what is the hard part about it, so that maybe newcomers can focus on that.

Sir! your teaching method very imprasive.i like it.and it become a very helpful for me.

What skills would you generally consider to be important to have for a junior data engineer roles? Thank you for sharing your thoughts Mike!

Thank you!

good insight. nice video.

This was a very realistic take on becoming a MLE, I’m switching careers right now. I’m taking a free prep course for a coding boot camp Codesmith CSX. Would you recommend a more efficient route. Codesmith is quite expensive sitting at about 20k.

Hey Mike, super informative and to-the-point video, much appreciated. I am currently an Electrical Engineering student at well known STEM school. My school offers an EE degree option with focus in Machine Learning and Data Science, and I’m wondering if this is something that sounds worth my time if I have aspirations to work in the ML field, or if it’s just a smoke and mirrors thing and I’d be better off pursuing something like Computer Engineering or even CS, or if they’re all viable means to an end and none is inherently “better” than the other. Keep up the great content!

Did you know that 80% of all the models built in the real world right now fall into two categories : they are classification and Regression Models. Did you know the top model for Regression classifications are a group of models called gradient boosters and not deep learning models. That's right, most real world machine learning is not deep learning

So, as a summary. Entry roles as data analysis or programming and learn python are the best way to start your way up to a Machine Learning position. Any recomendations for someone starting programming in 2022? Thanks

As you said, data engineering role is the top role in all of IT, should I become a data engineer or a machine learning engineer? If I should go down the path of machine learning, should I become a junior data analyst or a junior data engineer?

Hello, I have stumbled upon this video in a quora post, and would like to ask for your advice. I'm a first year high school student, that has immense interest in machine learning. To pursue this interest, I've started Andrew Ng's "Supervised Machine Learning : Regression and Classification" course. I've been enjoying it so far, and understanding little by little how things work is very rewarding. So I'd like to ask, what do you think is the best course of action I can take from here? I'd also like to add that: 1. while I'm taking this course I'm self-studying more math, as my current level of math is probably not sufficient. 2. The reason I took the intiative and started learning originates from me starting to self-study python a few months back. I'm fairly proficient with it, and have learned how to use several libaries, mostly related to web scraping . Some examples are: BeautifulSoup, selenium(made some fun bots with it too) and scrapy. Scrapy also led me to studying some basic SQL. I appreciate this video immensly, and hope you could reply.

Thank you for going straight to the point and for not beating around the bush. Very clear message. I guess you must be good at...INFORMATION CLEANSING as well 😂😂😂 I'll leave now

If someone has a basic understanding of python but not enough to be employable yet, in this economy would it make more sense to focus on studying for a data analyst role or a junior back end engineer?

Hi, Mike. Great informative video. I’m starting from scratch and was looking to get a role as a MLE. But what I understand from your video, it’s best to start out as a DA… learn ML as you build experience in the work force… then take the ML course, then apply. My question is, does your website teach everything to become a DA then move onto a MLE? And what is the timeline for something like that? Sorry for the long question and thank you for the information.

Awesome channel, followed and subscribed. Recent electrical engineer graduate and then did a data science diploma at bootcamp. The information in this 10 mins clip is priceless. Will save you so much time. Find an entry level data eng/data analyst role, gain skills in SQL and ML pipelines. I have a quick question how long do you think it takes to have a decent level of experience to then apply for more machine learning engineer roles on average ?

Let's hear from you in a video: How did you learn applied statistics and math for machine learning?

Thank you for your guidance. Where can we find data to practice data cleaning? Most datasets for online courses are somewhat clean and focus on modeling.

I was searching for data science and machine learning courses on online platforms since last year. Here my journey ends now. I am a mechanical engineer and have 6 years of experience in mechanical design and R&D. I am looking to further transition my career to a data science or machine learning engineer. Mike, please let me know that are those courses on your platform will be enough, or do I have to take some other courses as well? Guide me in this journey. Although I have already learned a decent amount of python from Udemy.

Thanks for the nice video! What do you recommend to someone working as a Data Scientist and wanted to transition into ML Engineer role?

@the data janitor thanks I've been stuck on your videos because for the first time someone who knows speaks the truth, I affirm this because I've been on the search for years, at least since after completing Andrew NG's ML course in 2020. I even had to enrol for a 2nd degree in Computer Science only to discover that DA is the gateway. What do you suggest, would the CS degree really be so much of an advantage?

The path you propose for Masters and PhD's doesn't work. Companies won't even reply to our applications for analyst roles because they're afraid we'll move on quickly. We get interviews more easily for data science roles, but then interviews feel like we're facing an extreme bias against us. I started programming at 8, was hand-assembling code to machine language at 11, then worked for few years as a programmer before college, where I used SQL a ton, then got a physics PhD, which was data analysis heavy, and then did a postdoc. I didn't go into academia because I don't feel up to it, I'm not that interested in teaching, and I could do my research nights and weekends. In a functioning society, it should have been easy to find a job relevant to my skills, don't you think? I looked for work in 2017-2019, failed, took a sabbatical to deal with the stress and heartache, and then started Doordashing during Covid. Now I'm on another sabbatical because I couldn't deal with the internal conflict that comes from Doordashing after a PhD and 2 years of failure at finding work. If it weren't for my fiance, I don't know where I'd be. My mental health, our relationship, and our long-term financial health have been ruined by this. What's blocking the entrance ramp is the fact that employees are using companies as jobs programs for their friends. Apparently, no one gets a job without finding someone to pull them in the backdoor. My PhD adviser told me this, and a recruiter as well, but I didn't believe them, even though I had already seen evidence for it from the inside of companies. It felt like they were telling me everyone's acting like a rat on a sinking ship. I felt that surely, between my ability and humanity's intrinsic goodness, things would work out. Turns out they were right. I had too much faith in myself and humanity. A portion of data science interviewers are lazy, superstitious, insecure, and downright stupid. They're looking for any half-baked reason to torpedo our applications, when the sum of what we bring would easily and obviously make us excellent hires in the intermediate term. Better hires than their college buddies, relatives, and interns. I've heard so much stupid shit from data science interviewers, like people with opinions they formed from N=1 samples, a guy at google who didn't know the geometric picture of how a perceptron layer works, a guy who told me I don't know what I want in life (don't tell me about what I want), and a guy who downright lied to his manager about an explanation I gave for gradient boosting. Whether a person gets hired has more to do with connections than ability. That's a bad thing, not a good thing, but our society celebrates it. If employers are worried about having to pay too much until we're up to speed, that's still on them, because as far as I've seen they don't want to actually have that conversation. In the early stages, they just want to know how much we're asking. They force it out of us ("It's just for this dumb form but we have to have it before moving on.") Then before we make it to actual negotiations, interviewers reject us (presumably because because we'd be too expensive and they already have someone they want to hire). It's a completely fucked way of going about it.

Heh... I'm a SQL and BI veteran/real world data dude/machine learning engineer... and Kaggle competitions expert... SQL, especially SQL with vendor extensions like T-SQL - it's like the bass guitar. The bass is one of the easiest instruments to learn, but it is one of the hardest to *master*. SQL is exactly like that... now the SQL you see in training courses... versus the SQL you see and need to use in the real world of business data.. don't get me started. BI languages like DAX in Power BI and MDX are very very similar... easily to learn, so hard to master. This guy knows exactly... and i mean exactly, what he is talking about. I don't think there's a video like it. But my take is there is more work doing that stuff in the world of analytics and business intelligence, than there is in the world of machine learning. And just because you've done DA100, doesn't mean you are ready to model real Power BI solutions either :)

I am going to take your advice and start as a junior python programmer or a data analyst role which will help me move up the ladder towards a machine learning role. Thank you for not using jarring graphics and dishing out pure facts. Hitting that Subs button now.

I mean, yes, these job listings all ask for SQL and Python etc.. skill but the also ALL ask for Masters or PhD degrees as well. So i'm confused here. Is it or is it not, reasonably possible to transition from a pure python/sql programming job to a Machine Learning or AI etc.. position? This was my current goal but I'd rather not specialize in Python and SQL if it's impossible without a degree (I'm already past 30 and can't afford to work full time AND earn a master's with a Lung Tumor. I don't want to waste my time, but I'd like to be optimistic. If it was possible with an associate's or perhaps Bachelors i might be able to pull it off, but there's no way I could pull 6 to 8 years of university.

HI this video was really helpful and may I know if there are any entry level jobs in data engineering field straight out of college thank you

Do you think asvance degrees like phd would help in a machine learning career? Companies like anthropic demand phd in a lot of their roles, is it the rule or the exception?

I visit you website thats great👏👏

Hi mike, thank you for always giving real world advice in real world job, I have a question, If someone want to do the programming path as an entry level role for machine learning, what would you recommend to get the first job as a junior programmer because i don't know any programming certification and i don't have IT background

This was such a good information, recently i started to do my ms in data science, even though i have 3yrs of experience as a software developer, when i looked for jobs they all require experienced people and i was confused did i choose the right path, or what next should i do to get into the right path

Great content; I love it. I'm in the second year of my Ph.D. in Compute Science, and my research is in Deep Learning. I wish I had found your video before I started my Ph.D. It's late for me to drop out of school, though. I also have 3 yoe of coding Python for my cloud security job. I know I will need a lot of SQL. Do you have any advice for Ph.D. people (AI research focus) to not waste time and start as a machine learning engineer? Thank you.

Although I am graduating with a masters this summer, I now know that it is not an important factor in becoming an MLE. I know the basics of SQL and have experience in Python and ML libraries. Would this still be considered as "starting from scratch" in the real world?

Hello Sir, love your videos. I am an CS undergraduate senior and did an SWE internship. Quick Question. You mentioned becoming a data analyst and then looking into being an ML engineer. Would a Back-End engineer also work to become an ML engineer in this case? Would the constraint be it needs to use SQL and Python? Your videos are eye-opening. thanks again.

Hello Mike, I am a Phd graduate myself in ML. Would I also have to start with data analytics role before attempting to get into ML Engineer position? This is the position I am ultimately targeting at. Thank you for the videos btw.

How proficient would you have to be in python to truly have be successful in ML?

Good afternoon sir,I'm 21 years old amd I'm looking into making entry into data analyst I came across ypte video recently about Starting with data analyst and then making a transition into data engineering I have to say I loved it !!! Sir so if i get a strong foundation in sql and power bi or tableau is it sufficient to get an entry level role in data analyst ?

Thanks for Awesome video, i am working as Senior Data Analyst (5 years XP) and wants to transition to MLE what would be the good learning course ?

Hello, very very helpful video sir, but I have a question. when I start with a data analyst role, won't I practice data cleansing well ?. so the only thing I need to do is to learn the modelling part ?

I have some quick questions, please. Would you recommend after getting a computer science undergrad, I go for a data analyst role or instead go into a python programming role? What is better? Do you recommend any certifications to compliment the job. Do you think getting a Master's in Machine Learning, only after getting work 2-3 years of experience, is good to make me more valuable? Any help would be greatly appreciated and thank you so so much.

As a high school student learning python and sql, should I pursue a masters degree in computer science to enter this job?

@thedatajanitor9537 I have some SQL (over 10 years), programming (C# over 10 years and Python 1 year), No experience with Power BI and I want a remote job in Machine Learning, and I am outside the United States of America; Do I follow the Logikbot shortcut on Machine learning or the Data Analyst role. Please guide me.

Great video! I'm in my last year of undergrad at a top 3 computer science school, trying to determine whether I want to do a masters. I'm specializing in vision, and most companies I have seem posting Computer Vision Engineer (also sometimes called Deep Learning Engineer or Machine Learning Engineer on a vision-focused team) roles require a masters degree + ~2 years of experience. I've also noticed that in the 3 companies I've done internships at, most engineers in these roles had masters degrees or higher. So, it seems to me like continuing to masters is the right choice, since companies seem to prefer this qualification for roles in computer vision. What is your take on this @the data janitor?

I am doing my PHD in industrial engineering. Machine learning is probably going to be my research area. Do you think it’s going to be more beneficial for me to become a data scientist first and then switch to Machine Learning? I am fairly confident I can get a data scientist postion ( a lot of people in my school have). My end goal is machine learning engineer btw. Any advice.

i am not able to pay for logikbot can u provide razorpay or some other payment options for indians

is there any entry level Data Engineering (DE) jobs?, after about a month I will graduate with a master's degree in Artificial intelligence and Data Science, I saw some articles and videos about DE and it seems like a cool job where your work is impactful and helps companies to grow! is DE a good choice?

I am QA engineer from 2 and half year.. i have knowledge about SQL then JAVA selenium automation tool .. currently learning ML - thrue python .. i can get entry into ML ? Can i eligible for little short cut ? Please ans

One question, I have the python professional certification, tableau data analyst certification, and excel associate certification. Where do you think I'd fit within my job search. I have no job experience and I really want to be a machine learning engineer. I do have machine learning skills but no certification yet

This is valuable knowledge! I was offered a free research based masters on top of a monthly stipend to do healthcare imaging segmentation work. I’m 25 and just graduated but I currently do web development. In your opinion can i do both as i get my masters or will the deep learning work require too much time?

Yesterday, I got laid off from my first-ever job as a machine learning engineer. I was there for all of 8 months. I was the only person at the company with the job title of machine learning engineer. From my very limited experience, much of what you say rings true to me. I graduated last year with a master's degree in data science after having having worked the first 50 years of my life in other fields. I began the degree program with zero experience in Python or SQL, and accepted a lower salary as a machine learning engineer because of my relative lack of experience. I struggled mightily, and will take to heart your suggestions as I look for my next job. I don't regret getting my degree and I don't regret my first machine learning job. I love learning stuff and I'll be checking out what you offer.

Hey, I’m months away of finishing high school, I’m 17, I consider myself pretty decent at math and statistics, I’ve been into coding for a few months (mainly Python), and by now I think I’ve decided to be an ML engineer. Thing is, due to personal reasons I’ll be forced to go to college, I’ll have the opportunity to choose between CS, CE, or SE, should I just go and choose SE since I think that it would be the least time consuming for me? (Considering that I’ll learn the vast majority of ML knowledge out of college). Thanks :)

Hi Mike, I am working as PowerBI developer in a MNC from last 2 years and I recently got opportunity to move to a data engineering project in same company. Should I take it ? My main motto is salary and I am ready to work hard.

I'm mostly interested in creative challenges like developing new tools that serve practical purposes like what you see on channels like Two Minute Papers. Do you know how people get into those sorts of jobs? I like to think that if I have lots of personal projects showing my problem solving ability and practical creativity towards developing new technologies that I could get a job somewhere, but I have a feeling that it doesn't work like that. I do this for fun and am not seriously looking for a career change, but I was wondering if you knew much about this? Nividia and google do quite a bit of ML technology development and that's what I'm most interested in. How did those people get their jobs, and are the jobs as glamorous as they seem? Thanks

I do not have a degree, but I believe I can easily learn any tech role. If I got the SQL, PowerBI and Tableu certa you mentioned. Will I immediately be rejected simply because I have no degree. I live in London

☝🏼☝🏼☝🏼☝🏼

I am a business analyst with over 7 years experience. I am very proficient with SQL, Python, data visualization tools, etc. I even taught myself machine learning and applied that at my current job (I created and validated an accurate predictive model and implemented in an application). Still can't get a data analyst job. Much less a data scientist or machine learning job. I have been searching for a while. Is it just the job market?

To be honest. Machine Learning feels like over hyped garbage algorithms. In bigger countries its useful but in smaller countries like NZ it is such a waste of time. Our data isn't even clean enough to make any of the cool data shit work well. 😒 It's embarrassing.

Hi Mike, I know this comment is abit late but right now Im going to take a masters in Data Sc at Monash Australia so that I will be able to migrate there quicky, but I understand what you said about the skills in masters to become a machine learning engineer is hard, so would you recommend me to take an external SQL courses on top of my masters so that when I graduate I can start immediately with knowledge in SQL?

only truth in this video, a PhD won't cut it in the real world nobody cares

Please, do not be over enthusiastic. The complexity in this career and how messy are the software, will make you quit at some point.