Data Science Roadmap 2023 | Learn Data Science Skills in 6 Months

do you want to learn data scientist skills sitting at home using online free learning resources in this video I am going to talk about six months roadmap where we will talk about both Technical and soft skills you have to put four hours every day in these studies where three hours will be spent in learning technical skills one hour will be spent in learning core skills I have included a PDF file that contains link of all learning resources along with week by week study plan exercises and Milestones I myself work for world's biggest financial data analytics company called Bloomberg here in New York USA for 12 years and this roadmap is based on my real life experiences two years back I published similar roadmap which received more than half million views and many people got a job by following that this video is five times better version of that old roadmap here is a roadmap PDF that you can download from video description below it shows core skills surrounded by two skills first two weeks you will spend learning python data scientists use python or r as a programming language I always suggest people to Learn Python because the language is very versatile but some people use r as well in Python you need to know only these many topics during your first two weeks okay these are the basics of python now python has so many topics so if you spend let's say for six months just in Python that's not gonna be wise so spend only first two weeks and in terms of learning resources I have this YouTube playlist so if you click on it you need to follow first 16 videos these are very small videos which has coding exercises everything right so when you watch any video make sure after watching the video you try to digest what you have learned and then you work on exercises these exercises are very very important so that would be your assignment for first two weeks okay and if you open this particular link you know let's say read write files uh here you have this exercise okay and there is a solution also but if you are a sensor student you will not look at the solution you'll first try to work on it on your own and then only look at the solution if you by the way look at the solution directly I have embedded some virus into it so your computer will start getting a smoke all right so make sure you are doing your due diligence now here I have mentioned track b as well so either you learn from free YouTube videos or you can take my course on core Basics dot IO for python now see while you can learn things for free if you spend little money and do this course you will be able to learn things faster there won't be any ads and there is uh an end-to-end project as well I compiled this with let's say you are going to Europe for a vacation you can use Google Maps and you can go to places it's gonna work but if you hire a local guide that person will save you a lot of time mental headache so three resources versus paid that's the difference okay so if you want to save mental headache and kind of have very smooth learning you can go for a paid course in terms of assignments as I said you will finish all the exercises and then you will create a professional looking LinkedIn profile remember I said that every day three hours you are spending for Tech skills but one hour you are spending for soft skills and the LinkedIn is the platform you want to be on if you are wasting your time on Instagram Facebook stop doing that they are not going to help you in your career spend half an hour every day in LinkedIn okay and then that Journey would start with you creating a nice looking uh profile some people have seen they post blurry picture and on LinkedIn you have a phone which can take a pretty good quality picture so take a nice head shot put it on your LinkedIn profile attach appropriate tag such as open to work etc put a nice Banner such as data science loading and that way you will begin the Journey of building an online presence okay so first two weeks are going to be relatively easier not much workload the assignments that you have are pretty simple when you work on this assignment make sure you are doing check mark that way you know you are achieving your Milestone now one thing I messages people do is that they do study in group if you go to gym let's say you're going alone it's not much fun but if you go to a gym with couple of friends it is much uh fun and you know you have that motivation and accountability as well so you can make buddies in your studies and you can go to my Discord server go to this partner and group finder chat there are so many people who form groups here and they study together that way you're holding each other accountable week three and four should go in learning pandas data visualization and when I say data visualization you will learn either matplotlib or c bond you don't need to learn both the libraries you will typically start with numpy YouTube playlist because pandas internally uses numpy so it's a good idea to have a good understanding of numpy there are just four videos which you can finish maybe in one or two hours then you will spend time learning pandas for that I have a YouTube tutorial playlist where you will only look at first time videos and that's it this playlist received close to 2 million views and I have explained all pandas Concepts in a way that even a high school student can understand it easily pandas is a library where data scientists spend their time doing data cleaning data exploration you have heard that right 80 percent of the time data scientists will spend in doing data cleaning and data exploration so that's where this pandas Library come in play so it's a very important skill matplotlib allows you to do data visualization for that also I have a nice six seven videos tutorial playlist which again you can finish in less than two hours now once you have learned numpy's pandas and matplotlib you need to now spend time on your core skills which is LinkedIn on LinkedIn I'm suggesting that you start following two influencers so Dalian Aloo sees a data science influencer civil data scientist at Amazon and she writes very nice meaningful post which will help you learn technical skills as well as soft skills associated with data science career you can go to her profile and click on see show this all activity and start reading all this post okay and this post will be all right let's say She interviewed this person who was Hercule at AWS right so this is a data scientist working at Amazon talking about their experiences then she talks about various you know career related aspects of data science career as well so you can start following uh these influencers the other influencer is Haman vadivel who's a data analytics manager he's also my business partner he spanned more than five years working at edgewell Europe and he was a data analytics manager so he has done some serious industry work and if you look at his advice on LinkedIn it is super amazing so for example if you're learning a tool without knowing how it is applied then you're doing it wrong right so all these posts are allowing you to learn new skills and more importantly if you start engaging let's say I start commenting on it what will happen is when you engage you can interact with other data analysts who are working in the industry lesson pal he's a data analyst working at this industry or let's say you look at any dalyana lose post you will find so many data scientists who are commenting on her post so when you let's say let's say I reply to this person this person is a data scientist now I'm kind of building a connection with that person and if we have a few such interactions and then if I send him a LinkedIn request he'll probably accept it and then we have built now online friendship tomorrow when I'm looking for a job unless if this person's company has an opening this person will not mind to refer you and whenever someone is referring you it becomes very easier you will at least get an interview call I was at Bloomberg 12 years and in media for a few years and I was myself in the interview panel so when I was interviewing so many people if someone from my team suggests me that okay this is the profile you should interview I would schedule an interview call usually so restaurants goes a long way another benefit of meaningfully commenting on LinkedIn post is that you will be learning and you will be doing brainstorming with other people all right so I have highlighted both the benefits here remember that online presence is a new form of resume okay there are some people who don't have resume in their online profile is so strong they will get an interview call from the companies and usually they get selected so once again online presence is a new form of resume now in terms of business and soft skills remember that in the diagram that we saw earlier business understanding is one of the most important core skills for a data scientist and to build a business understanding there are few YouTube channels that I would suggest you follow for example this one right things cool so this channel uh this particular video is about how amul which is a dairy company in India they beat the competition during covet times so this person will do the thorough business case studies almost like a business case study where he will explain everything from data analytics data science kind of point of view he'll put various numbers he will explain basic concepts related to a particular business in a very simple language so by watching this case studies you are building your business understanding another thing you need to do is you can go to Discord and you can start asking questions okay so for example I have this Discord server and this core server is basically like a group chat where there are thousands of people for example in my server there are 20 000 people okay and if you have question related to python you can go to this and you can ask the question and there are so many community members for example python underscore guy this guy is very useful you will generally answer and there are so many other people also who will help you so you can start asking questions in a meaningful way now look asking question is an art okay and I have talked about that in my LinkedIn post so how should you ask question don't ask for spoon feeding right don't just say I'm facing this problem can you help me if you post this kind of question people don't want to help you but if you say unstuck here despite trying x y z any tips for further troubleshooting here you are not asking for spoon feeding here you are asking for a direction and you have tried XYZ that shows that you heard done your due diligence okay so asking question is an art and that is another important soft skills that you need to learn by participating in this course in terms of assignment you need to comment on at least 10 data science related LinkedIn post and your comment should be meaningful don't just say nice post thanks don't just say that okay write a meaningful comment where you are expressing your genuine thoughts related to the content in that particular LinkedIn post the other assignment is you need to note down the key learnings from three case studies so you can use things cool you can use any other YouTube channel of your preference and note down a summary of key learnings from the three business case studies and share that with your friend who is part of your group remember I said that in Discord you can go to partner and group finder Channel make a group and in that group you can have weekly Zoom call and you can check in you know and say okay this is the case study I looked at and these are the learnings and then you can discuss it as a group you will spend week five to eight which is one month time period in learning statistics and math for data science for this I highly recommend Khan Academy's statistics and probability course this is a free website you don't see any AD nothing and you can study various concepts related to statistics and probability for example interquartile range now this is the approach that data scientists use for removing outliers and here you have nice very easy to understand videos and along with the videos you will have this kind of interactive exercises all right you're getting all this for free so all you need is willpower and a determination to learn things if you look at the whole course it covers a lot of required Concepts that you need for data science such as Z scores percentiles right various forms of distributions probability random variables sampling distributions are significant test and so on now while you are following that course if you have any questions or let's say some ideas not clear you can go to statquest YouTube channel this is a popular YouTube channel for statistics let's say you don't understand histograms so here he has explained histograms very clearly Jaws timer is a very good teacher and he visually explains Concepts in a way that you will immediately get it once you have finished this course Khan Academy scores you can follow my playlist for Math and statistics for data science on YouTube now this playlist talks about some of those Concepts but the difference here is that you will see python code as well right so here I'm explaining let's say mean mode percentile Etc but then I will do python coding using the same concept not only that you you will have an exercise as well so if you go to video description and look at the exercise there will be a problem statement and there will be a solution link as well so this way you are kind of practicing the concepts that you have learned so the assignment for you in this month will be finishing all the exercises in that particular playlist and then performing Eda which is exploratory data analysis on at least three data sets on Kegel now if you're learning data science you have to know Kegel you can't survive without Kegel this is a website where you can find variety of data sets you can find code discussions Etc so let's say if I go here and if I you know exploratory data analysis if I type this I will find a lot of notebook jupyter notebook so jupyter notebook is basically your python code where people have done exploratory data analysis so here you can download your data this is let's say cardio good Fitness data that you can download you can perform data analysis using the statistic skills that you have learned in this month as well as Panda skills that you have learned previously okay and you can also look at the solutions which other people have posted so this way you are kind of having guided learning let's say if you get stuck there are solutions there are notebooks available for example this person has done analysis of treadmill users you will see the whole python code the whole notebook you know where he did all this data visualization and so on week 9 to 12 one more month you will spend in learning machine learning here in machine learning uh the important concepts are regression classification clustering feature engineering and so on for this there is one stop resource which is YouTube playlist that I have if you look at this playlist this has received more than 2 million views you can read the comments in the videos you will know why this playlist is very popular I am explaining machine learning in a very very simple language even high school student can understand it easily and then I have Concepts python code and exercises too so it's a complete package in this playlist you need to follow first 21 videos because after 21 videos there are projects and here you will learn the basics of machine learning right like linear regression gradient descent how to split data into train test various classification techniques uh clustering techniques and so on I also have a feature engineering playlist which has only four videos which is probably more than enough and then you need to know about some project management tools all right so in this one month you're spending three hours every day right so that will go in machine learning but every day you are spending one hour in soft skills so that one hour will go in learning project management now in majority of the companies people use agile as a project management methodology and in agile there are two main techniques scrum and kanban first crumb I suggest that you see all the videos on this particular website these videos do not have any AD and you can watch all these videos in I think less than one and a half hour okay very easy to learn the second technique is kanban for which I have included one video and kanban is really simple technique so I can explain you right now for example this is the real data analytics dashboard that I have for my own company at lick and here you have four swim lens swim lens means the first one is to do so all the tasks that we want to do in our company will or on a project given project will list them down here okay but now we need to prioritize them and we can't work on all the tasks right so we pick higher priority items and we move them into in progress status and when we move in in progress status you can actually assign someone so let's say I want locky lol to work on this particular project and when this task is assigned it is in progress now this person will work on it whenever task is complained they will move it to test status and in test either the QA person or someone from product will test that feature and once it is tested they will move it to done so it is just you know progressing step by step this is kanban this is called kanban board people use jira notion variety of tools there are 100 tools available where you can do project management the one that I showed here is a very popular software called jira when I was at Bloomberg we were using jira all the time in terms of assignments you need to complete all the exercises in the machine learning playlist okay so that is number one you need to then work on two Kegel notebooks related to ml so once again if you go to kegel.com you can go to code data set so if you look at all the data set let's say I want to look at the data set on classification okay and in the classification you have mobile price classification for example now see so many people have submitted their code and if you look at any notebook here let's say this one is using random Forest uh here in the code you will find so this is data and in the notebook you will find the actual course so see SQL on random Forest so that is something that they have used so I want you to look at two data sets and build ml Solutions so you'll be you'll be building basically jupyter notebook to solve that particular problem and you can what you can do is you can take one classification problem and one Recreation problem the third exercise you have is you will write two LinkedIn posts on whatever you have learned in your ML and even pandas Journey okay in the LinkedIn you can say okay I went through ml lectures and I learned these many things and you can ask your friends to engage sometimes you know some data scientists working in some company will comment on your learning maybe they will correct you they will give you advice so that way you're building connection and learning at the same time the fourth exercise you have is go to Discord and help with at least 10 questions now when you help others with their questions you get a huge benefit now don't think that you have to be expert in that when I was at Bloomberg I was part of our Discord group internal Bloomberg's Discord group and if someone posts a question and if I don't know the answer what I used to do is I will spend my time in finding the answer for that person this way first of all I have learned that Concepts in the future if I am facing that error I know the solution so my technical knowledge got very solid second when I help someone that person will feel thankful okay so I built a relationship good relationship with people so what can happen is this code let's say you are helping someone and let's say that person gets a job is working as a data scientist tomorrow if you're looking for a job that person will be willing to help you because you help them so these are the four assignment that you need to complete and check mark once you have completed them then in next three weeks you will work on two machine learning projects one is a regression project the other one is a classification project so for regression I have this YouTube playlist for Bangalore property price prediction where we built an end-to-end project okay where we covered data cleaning feature engineering model building python flash server we even created a website and then deployed it to AWS now if you look at this particular first video you will notice that the website that we built what it would do is you can enter you know square foot path how many bedrooms location and when you click on estimate price it will tell you what is the price of a given property this is truly end-to-end project uh something you would do in the industry we cover deployment and average thing okay and we have the entire GitHub repository with the code and everything so if you check video description you are going to find code and everything so it's a very it's a guided project all the help the second project is a classification project where we did a sports celebrity image classification here we covered data collection data cleaning feature engineering once again deploying it to AWS and so on and you know this project is interesting if you love sports especially because we classified all these five celebrities you can use your own favorite sports celebrity or maybe let's say you want to do movie a star image classification or the classification for your friends and family you know you can do that as well code and everything is given so the assignment that you will have is first of all instead of using flask you will use fast API so first API is a latest web framework which is better than flask so I suggest you use fast API in this project and for fast API I have this one video it's super easy to learn so if you watch this you know less than 20 minute video you will understand what fast API is the second assignment you have is instead of property price prediction take any other problem statement from Kegel but that has to be related to regression okay and the third one is for classification uh once again you can do classification of any other image data set or if you want to do person classification maybe you do friends and family image classification and then deploy to AWS or sure so this way you are building a unique project for your resume whenever you add these end-to-end projects on your resume they are going to make a solid impression on interviewers mind but you don't want to blindly copy someone's project correct you want to add your own customization and these are all the customization idea that I have given here next two weeks will go in learning SQL as a data scientist when you are building a machine learning model or doing exploratory data analysis the first thing you need to do is connect with a data source and pull necessary data in your jupyter notebook or python codes often organizations will have their data in a relational database and whenever you have data in relational databases like Oracle MySQL Microsoft SQL Server Etc you need to know SQL because using SQL queries you will be pulling the data in SQL also you don't need to know the whole world you need to know only these many Concepts don't go into craziness of triggers and indexes and all those things because data scientists do not do that data scientists are mainly reading the database okay so for that reason you need to know all these Concepts once again Khan Academy has a nice course there is another website called w3schools.com where you can learn SQL the third resource is SQL bold where you know you can interactively practice for example here I can say select me all the movies where your is equal to 1995 and on on flight is changing the results so I pretty much love this website now while you can learn from three resources your learning will be limited because SQL bold for example it doesn't go into all the concepts in detail W3 school has all different concepts but there is no structure learning so if you want to spend little money and get a structure learning especially if in terms of SQL for data professionals then I have this course now all the reviews on this course by the way they are real I don't make up reviews just to increase my courses and the beauty about this course is that we have used industry style end-to-end projects so this ethnic Hardware project that we have included has one and a half million records and as I said before I have 12 years of Industry experience working with Bloomberg I have my own data analytics and software company where we work on client projects based on that industrial knowledge we have built this course and all the explanations are super easy to understand at the same time you have a lot of exercises quizzes as well and then there is a movie style learning so that you don't get bored right we are using this uh Peter Panda concept where Peter panda is a Most Wanted data scientist and we are walking you through the Journey of that person and that Journey resembles your journey so you can check it out in terms of core and soft skills presentation skills is very important for a data scientist because data scientists will do their work in Jupiter notebook or whatever tool they are using then they will make a nice presentation and they will tell their data story to project stakeholders here having a good presentation skills is extremely helpful and for this I recommend you watch just one video you don't need to watch anything else just this one video is enough watch this video maybe three times and try to incorporate all these concept that he has taught in your PowerPoint presentation in terms of assignment you need to practice at least one resume project okay so now code basic dot IO is my website where we are scheduling project challenges every month these are all free anyone can participate and in these challenges we give a real life data set and problem statement for example this one is in fmcg domain this one is in Hospitality this one is in Telecom domain now we have connections with industry expert for example for Hospitality domain we consulted with a person from Oyo rooms all your rooms is a big Hotel chain in India and Asia and we got inputs from that person and created this data set this problem statement so while working on this project you are getting understanding of that particular business you know it could be Hospitality Telecom retail whatever and then you will work on this particular Challenge and then you will post on LinkedIn whatever you have created so you might have created let's say power bi dashboard we are going to also start SQL challenge in few weeks so by the time you're following this roadmap SQL challenge will be up and running on this website and when you post your learning or your submission on LinkedIn what will happen is people will start engaging so I'm just showing you a sample post by the way so Satya she posted this resume project challenge related LinkedIn post and here see so many people interacted 200 260 when I interacted now my LinkedIn network has more than 100 000 followers so when I am commenting or liking this post this will show up in the feed of all those hundred thousand people and those people might be HR managers or data analytics manager they might contact you for an interview we spotted Talent from satyan look at her profile now she's hired in our company so we hired total four people who were participating in this challenges and we hire them without the interview now this might be surprising for you right how can you hire a person without the interview we hired them and we are happy with their performance because when we looked at their LinkedIn activity number one we are getting clues on their return communication okay so just by reading this post you can get some Clues on return communication by watching their video presentation some people even record a video and post it you can get an idea on their presentation skills their verbal English skills and the same people were participating in this course so we got a lot of understanding of their people skills their you know like team skills and so on and when you look at the dashboard you are obviously getting idea on their technical skills so this is very very important make sure you don't skip this particular assignment the other benefit is that the top 10 or 20 20 performers in this resume challenge we send their profiles to selected employers with whom we have a relationship with okay so we have lot of Industry contacts in my company core Basics and we send these profiles to those employers so these people are going to get multiple interview calls I also write specific LinkedIn post on these people so let's say these 10 people were the winners okay in the project challenge so I wrote this particular LinkedIn post now what happens is once again so many people interacts is 60 000 impression so your profile is going to 60 000 Impressions so again you're building this online presence week 18 to 20 you should focus on BI tool either power bi or Tableau now people have this confusion should I learn power bi or tableau if you ask me I always suggest power bi because there is this a third party research company called gardener and they did some research and found that Microsoft is leading the game recently Tableau they announced job cut as well because they're not doing good and Microsoft is penetrated so deeply into so many organizations power bi is going to be a clear leader so there'll be more power bi jobs in the future they are already increasing so learn power ba now you have to option track a track B track a is free where you can follow these three playlists and these are Project based power bi learning playlist the first one is sales inside now this playlist has helped many people get a job so I'm going to just show you one LinkedIn Abbas srivastava he said that your sales inside project series help me in getting a job trust me I have so many people who have sent me this message so this playlist was created by me and my friend Hamilton we both have real industry experience and this kind of outlines how the project is executed in the industry so you can learn using these three projects the second one is your personal finance dashboard where you maintain your personal income expenses Etc and the third one is HR data analytics project now here we have used a real life data set so at link is my company we have more than 70 employees and we used employee presence data we must certain confidential fields and then we use that data we invited HR manager of my company here and we did this project so these are the three projects to learn for free if you want to spend some money and you want to have smooth and like high quality learning see free resources are also high quality but this is like super high quality learning then you can follow this power bi Course once again all the reviews folks are real we are very honest here and we don't play all marketing gimmicks like sales offer this offer that offer the pricing is really good this course is worth 30 40 000 rupees actually and we are selling it for only 2000 rupees so 110 the price very affordable we have completed end-to-end project we have covered a lot of project management project planning nuances you know how a kickoff meeting goes for example when you're working in the industry how various stakeholders discuss various aspects and then we build a super amazing uh dashboard that solves uh real life problem basically and this project covers business domain knowledge technical learning soft skills it's like a complete package you'll see resume interview tips deployment all of this and this deployment etc those things you won't see in the free tutorial playlist you can learn Tableau as well as I said before I would go for power bi but let's say if you have some reason to learn Tableau I have Project Playlist in Tableau as well in terms of assignment you will participate in one more resume project Challenge on my website codebasics dot IO we already talked about it and then you will post your submission this time using video presentation so previously you can post submission without video presentation this time use video presentation for example this is the post by Naveen he outlined whatever he did in this project as a text post and then he created this particular video presentation okay and if you look at this video presentation he explained the problem statement as if he is presenting this two business stakeholders and then he showed his solution it's like a project demo and then he outlined all the insights that he generated out of this project okay so by watching naveen's post actually we detected his talent and we hired him in our company so once again data analyst at ethnic technology so this person is hired in our company and we did not take an interview we just had a normal phone call we talked about few other things but we did not ask any technical questions so these resume project challenges and Linkedin posts are going to be beneficial to you you can continue participating in Discord server once again make sure you're working on these exercises and check mark in all these boxes you know learning all these things is like learning swimming if you watch a video of someone swimming you're not going to learn it you have to jump in the pool similarly check marking these items is like jumping the pull and practicing week 21 and 24 the last month in your journey you should learn deep learning now you might be thinking there are so many things to learn but data scientists rule is such that it requires diverse set of skills if you look at any data science job specific job you will realize that they might not be using all the skills there are data scientist jobs where you use only Excel and power bi so it's more like a data analyst job but they call it data scientist there are jobs where you are using python in some form of machine learning but you don't use deep learning then there are other jobs where you are using mainly deep learning okay but I'm telling you all these diverse skills so that when you're applying for the job you get an interview call if you have all these diverse skills eventually what will happen is once you start working on the industry you will do specialization in two or three skills and you will focus only on that so although it looks like you're learning too many things this is like you're setting your general base and then that way you can get interview calls you can get your first job and after that job you will specialize or you'll focus on few Technologies out of all the that I have mentioned here now talking about deep learning I have a this YouTube playlist again very popular more than one and a half million views you can follow all the videos in this playlist right so I talk about a lot of different deep learning related Concepts starting from a very very beginner phase and I have used tensorflow but people use pie torch as well but this playlist will be useful to you anyway because some of these videos have nothing to do with tensorflow Pythons for example what is neuron you know what is neural network so I'm talking about General deep learning Concepts so doesn't matter you're using pythons or tensorflow you can still follow it this playlist also has Concepts coding and exercises then you can work on end to end potato disease classification project this is also one of the popular projects on YouTube where you are building a mobile application so let me just show you so the application will look something like this where you will open the application you will take a picture of a potato plant and you will send a message now it will call back in and backend will have a machine learning model which will do image classification and it will tell you if this potato disease has a disease see this one has a early blight decision early blood is the name of the potato disease so you are building this application is it is truly end-to-end project where you are using convolutional neural network so you start with data collection pre-processing your building model then using fast API as a web back-end building website building also a react native application and then you're deploying this model to Google Cloud so previously we use AWS now you are using Google Cloud so that way you are getting understanding of different Cloud platforms as an assignment instead of potato plant images you can use tomato plant images so the same data set that I have given in that project has tomato plant and I think green paper plant images also so just use that okay instead of gcp deployed to azur okay that way you're not blindly copying the project you are using that project as a template as a guide but you're building your own unique project which is going to look very good on your resume and once again create a presentation of whatever you have learned and post that presentation on LinkedIn now see in this six months you have learned all the fundamental skills required for data scientists so you build a very strong base but your Learning Journey should not stop there I'm still learning every day I spend one or two hours in learning new things so week 25 onwards your focus should be doing more and more projects you know don't try to learn this fancy framework let's say if you learn tensorflow don't try to learn Pi torch I mean if you learn one framework is good enough don't try to learn all these new and New Concepts instead focus on projects so build more projects focus on building online brand LinkedIn participate in Kegel competition build a good Rank by the way by having good rank on Kegel people have got a job let me show you so I interviewed tunnel Singh who was a mechanical engineer actually so if you say code Basics mechanical engineered to ml engineer you will find a video this particular video where tanu Singh was a mechanical engineer he kept on participating in Kegel and based on that he got a job as a data scientist see he did not have computer science degree on mechanical engineering degree his first job is directly data scientist he I think got multiple job offers because he had a good rank on Kegel similarly Discord you know be active in Discord do open source contribution these are excellent things you know these are more important than your resume now resumes are dying but they're not dead yet so if you want to prepare a resume I have a nice video I have given some templates you can download and you can fill in your information I myself was an interview for a long time so these are based on my real interviewer experiences then job application and success okay so I hope you can follow this roadmap you can get success in building a data scientist career now I want to talk about very very important topic here which is tips of effective learning the mistake that people make nowadays is they are lost in abundance abundance means if you go to YouTube you find so many videos on data science learning right you'll find so many videos on machine learning and so on people watch one video then second video then they go to tours data Science Blog they keep on watching this consuming information you should consume less information and you should digest more okay so let's say I watch one video on doing classification using random Forest after you have watched the video put away all your distraction and try to digest the information okay so digesting is number one second Implement write code Implement see how it works third once you have implemented share it with your friends you already made a group right I have mentioned using partner and group finder you have already made a group in your group try to share your learning or go to Discord and if someone has a question and if you know the answer try to help them when you help them your understanding becomes solid in your brain so spend less time in consuming information which is input more time in digesting implementing sharing this tip can set you apart from rest of the crowd 99 of people are spending more time in input less time in output you should spend more time in output less time in input I have few career transition stories which I have highlighted here you can watch it for inspiration for example I interviewed a petroleum engineer who became a data scientist now this person's story highlights that domain knowledge is very important there's a company called Halliburton which is a petroleum company based in U.S when they were hiring they specifically were looking for petroleum Engineers because for any company domain knowledge is super important so if you're a petronum engineer or let's say you have supply chain degree or let's say this person here a degree in geology he got a direct data science job offer because that domain knowledge is very important sometimes people want to become data scientists they say oh my old experience will go in West no that is a solid base you can use to get a job now coming to Advanced topics you will see many people saying that oh you need to learn ml Ops you need to learn NLP computer vision in my opinion these are all advanced concepts I agree there are jobs where they hire data scientists for NLP specifically and if you want to learn NLP once again I have a nice playlist you can watch comments and Views and you will understand the quality of this tutorials this has again concept coding exercise everything the whole package but the reason I'm calling it Advanced topics is you don't want to get overwhelmed by learning so many different topics see whatever you learned in six months is already more than enough it's too much information you don't want to start another NLP playlist or ml Ops playlist and just put all that you know bulk of information in your brain therefore I would suggest unless you have mastered those six topics don't look at these look at these whenever you have finished those and you are getting some extra time all right once again this PDF is included in the video description now folks I am putting lot of effort in building these videos these road maps I left my very high paying job which I had at Bloomberg New York and I'm helping Community I'm building my business pushing my passion for teaching I would be very thankful if you can click on that thumbs up icon also subscribe to my channel because so many people who are watching the channel they are not subscribed so subscribe to channel click on thumbs up icon and if possible share this video with your friends so you can share it on WhatsApp you can also share it on Facebook the most important place to share this is LinkedIn so you can go to LinkedIn and just say hey I watch this video I found it to be useful if you are learning data fans follow this roadmap do this if you find this video to be useful if you don't find it to be useful then let me know in the comment if you find it too useful then also let me know in the comment but don't sit idle give me the feedback and help me reach more and more people thank you very much I wish you all the best [Music]

Channel: codebasics

Views: 261,823

Keywords: data science, data science roadmap, data science course, data science for beginners, how to learn data science, data science roadmap 2023, data science roadmap for beginners, data scientist, learn data science, data science tutorial, data science roadmap 2022, data science career path, learn data science step by step, data science career, what is data science, learn data science roadmap, data science learning path, complete data science roadmap, data scientist roadmap

Id: eaFaD_IBYW4

Length: 48min 29sec (2909 seconds)

Published: Thu Jan 12 2023