Step by step guide for data analytics

Do you want to learn data analyst skills, and you are not sure where to start? In this video, I am going to provide 3 months step-by-step roadmap to learn data analyst skills, assuming you do 4 hours of dedicated study every single day. Now you don't need to have any prior background. You could be a mechanical engineer or even a person working in totally different non-technical field. You can still follow this roadmap using online free resources, do 4 hours study every day, and you can learn essential skills that can help you become a data analyst. The first skill that is needed is Microsoft Excel. Believe it or not, in the industry Microsoft Excel is till date the most popular data crunching tool. So if your data set is smaller, most of the time data analyst and data scientists will be doing some type of data analysis in Microsoft Excel. Now you need to know certain features such as basic Data filter functionality, Functions, Vba Macros, Pivot table, doing basic charts and plots, and things like that. Your first Excel data science project could be managing your own personal finances. On Google docs there is a template gallery for personal finances. So if you click on this link, you will find these templates where you can track your monthly incomes and expenses. So if you click on let's say monthly budget, you will find this Excel file, where you can enter all your monthly expenses and then it will tell you how much money is left after doing all these expenses. So you're doing subtraction basically, and you can also maintain detailed transaction. Now in this Excel file, if you look at any of these cells you see the formula at the top, at the top. So these are the formulas that you want to learn, so that you can create nice visualizations like this, because as a data scientist or data analyst you will be involved in creating these kind of visualization charts and so on. And working on your own personal finances help you with that. You can also do annual budget tracking, where in one sheet you are maintaining all your monthly expenses, on children, debt, education and so on.

In the other sheet you have all your income, and then you get a nice summary. So if you look at these charts right, see they have these formulas. So these are the formulas you want to learn. If you look at like different cells, you will see how they come up with these kind of interactive visualizations in Excel, and what you want to do is, you want to create your own Excel file that can maintain your monthly expenses and income. And in the end you can plot the trends in which month you are having the maximum expense, what is your trend of income overall, month-to-month is it increasing or not? So all of this you will be able to do in Excel and in the end you are producing a tool which is helping you. So this gives you a mental reward and you can continue on your learning journey with passion. There is this another website which has a lot of templates. So I I downloaded this family budget planner, and if you look at that, you will see nice a planner like this, where you can plot even these kind of bar charts. See, if you look at this bar chart there is some formula being used and this is the formula that you want to learn. So if you fill all these numbers here, you will see these charts being updated. So your goal is to take inspiration from these files, and you create your own uh budget tracker, that will be the best beginner Excel project that you can work on. There is a YouTube channel called Chandoo, and I suggest that you learn Excel things from here. This guy is great he explains Excel really well. He also has this website called So if you are looking for any Excel related help, refer to this website and a YouTube channel. While you're learning Excel, you also want to tackle statistics because statistics is used everywhere. So the first resource I suggest is Khan Academy's basic course. So if you look at this course, it has a very nice explanation using visualization.

It also has exercises. So make sure you complete this course, and you will learn basic things about what is normal distribution, the inferential statistics, the descriptive statistics, probability, the sample distribution, uh summarizing quantitative data, and so on. These are the concepts you want to start with, and as you do more projects you can learn advanced topics. There is also a YouTube channel for Khan Academy. So if you are if you like watching YouTube, you can watch the videos here as well. But if you want that course, you will get a benefit of doing exercises. So I suggest doing that versus a YouTube channel. There is another YouTube channel by MartinStatsLectures, this is also another great platform where you can learn things like different kind of charts, histogram and density plots, box plot is used for outlier removal. So you want to learn all these basic things. The other channel that I suggest is Stat Quest with Josh Starmer. This person explains complex concepts in a very simple manner using visualizations. So if you have any doubt on statistics, any topic you're not sure about, please refer to this channel. After spending first 2 weeks in learning Excel and statistics, you should spend next 3 weeks which is week number 3, 4 and 5 in learning BI tools such as Power BI, Tableau and Qlik Sense. These are the 3 most popular tools in the industry. But you can learn just 1 or 2 tools. Even if you learn 1 tool, that should be good enough. Now these tools allow you to connect to different data sources. It could be Excel, MySQL or MongoDB, and you can pull the data and build dashboards, and different analytics. So for BI tools, as I said 3 weeks. If you want to learn Power BI, I have a complete Power BI sales insights project series, where I took a real-time scenario, real life scenario and I work with my friend who is working for a data analyst company in U.K. and we together did this project. So this project is solving a real life problem using Power BI, and this project it covers uh how projects are executed in corporate environment, in a professional manner.

So doing this project series will not only learn you teach you the technical skills, but it will give you a glimpse of what happens in the corporate life. So you you build some soft skills as well, such as project management for example. We we talked about Aims Grid in one of these initial videos. So that touches based on how projects such as data analyst projects are managed overall. For Tableau you can follow this particular playlist. For Tableau again, there is another playlist that I recommend you follow. So you can just look at this playlist, these are available on YouTube and you can learn these things on your own. Now one thing to keep in mind is that, you want to spend only only small amount of time in each of these topics, and you want to move on to the next topic. It's not like you spend six months just learning Excel and statistics. You should just have some basic knowledge, move on to the next topic, move on to the next topic and at the end of the 3 months, you would have covered uh the basics of all different topics and then you can start working on projects. Projects are very important. So your learning will be a continuous process. It's not like you learn these things for 3 months and and that's it. You will be constantly learning the the the new things. But these 3 months base learning will set a solid base for you, so that you can continue your journey smoothly. The next important thing is Python programming language. Sometimes people prefer R as well, but if you're confused you always go with Python. You want to spend week number 6 and 7 in Python. Now these 2 weeks you will learn just the basics of the programming language. Now many people are afraid of programming language. They'll be like, "Ooh! How am I going to learn it? Coding is not my cup of tea!" Well Python is very very easy. Even a high school student can learn it.

So give it a try. Remove all those biases that you have in your brain, that you are not made for coding. Python is like English okay? It's super easy. So just do it, do not give excuses. For Python, I have a very easy to follow tutorial playlist. So if you click on this link, you will find this list where you need to follow only first 16 tutorials. Now I have exercises as well for these tutorials. So if you go to this particular folder, you see this folder, and if you go to all these individual folders, for example read and write file, I have an exercise here. So after watching the video if you do these exercises, it will consolidate your understanding and your Python programming improve by whole lot. If you want to see Python tutorials in Hindi, then I have Hindi tutorials as well. So you can just say Codebasics Hindi Python, and then that will show you my Hindi tutorials. So these things are very very easy. It can be done in a matter of 2 weeks. You should spend next 2 weeks, week number 8 and 9 in learning Numpy, Pandas and data visualization. Numpy and pandas are essential libraries in Python that allows you to do data analytics. For example Pandas has a thing called a dataframe which is a two dimensional, it's it's a two, it's a table actually which allows you to do SQL type operation in memory. I have a playlist for both of this. So if you look at Numpy, like 4 videos 10 minutes. It shouldn't take you long time to go over this. Then for pandas you need to follow only 9 tutorials. I have complete list but only first 9 videos are good enough. After you learn Numpy and Pandas, you also need to learn about visualization library. You can learn either Matplotlib or Seaborn. You don't need to learn both, and I have tutorials for both of it. So Matplot and Seaborn and Matplot again. 7 videos 6 minutes each. So friends how much time does it take? Like 6 minutes each, 7 videos 40 minutes you will be done! After you learned all these skills, it's important that you apply those skills to solve on some projects.

For that I recommend you go to Kaggle and look at all the notebooks and the datasets that we have. See if you go to notebooks, you will find many notebooks. There will be many notebooks which will be for machine learning. You don't need to worry about machine learning as a data analyst. So look at the notebooks which are focused on data exploration and data analysis. Usually when you're doing machine learning project, like the first part of your project is always data exploration. So just do that and skip the machine learning part. You can find many public datasets in Kaggle, so you see U.S. Election dataset. So take these data sets and try to do analysis in Pandas, Numpy and Matplotlib. After you spent 2 weeks on this, the remaining weeks should be spent in learning SQL. I mentioned MongoDB here, but it's okay if you don't even learn MongoDB. Now let me close all others tabs. Now for SQL, Khan Academy's SQL course is highly recommended. Here you will understand the basics of relational database, what is primary key, foreign key, joins, relationship between the the table, the SQL queries and so on. Khan Academy is very good, it is a non-profit uh portal. It has videos, exercises, it is so good! It's very easy to understand, even even a stupid person can learn SQL so easily by following this course. And there is this Kudavenkat playlist, which I rec keep on recommending all the time. Here also you need to watch only first 16 videos. Now this 3 month learning is not just about technical skills. You need to learn some soft skills. So the first thing is how do you learn anything effectively. For that I put together a video, where I'm talking about basically spending less time on input, and spending more time on output. This is based on Nishant Kasibhatla's theory on how you can learn anything really fast. So watch this video, simple 4 minute video. But you will learn how to learn things very effectively.

So when you start this 3 month journey, the first thing is watching this video, so that you can follow that discipline during remaining 3 months. Group learning is very important. If you try to learn these skills on your own, you know you might be get demotivated. So for group learning, I have this discord server where you know accept the invite whatever, where you can find different channels on my discord server, and you can find uh your partners. In this partner and group finder group, you can find partners and you can make a group and do this study together. Having a partner will uh create an accountability. Also, if you have question, you can always discuss. So if you do group study, it is always always the best thing. I have different other different channels, where you can you know discuss different topics such as Python, SQL and so on. So make use of this discord channel. I have also mentioned different books and resources: Think Stats this is a free PDF book on statistics. Another good book on statistics is Naked Statistic. This is not free, you have to buy it. I also have videos on see I have like 4 videos on mechanical engineers uh transitioning to data analyst. For example this video I did with my good friend Hemanand, who is a data analyst manager in a company working for a company in U.K. He mentioned his story about you know how he transitioned from mechanical engineer background, to a data analyst background. I have another video of Chinmay who also did the same transition, mechanical engineer two data analyst. And then I have a video with Hitesh where he transitioned from B.Com to a data analyst. So by watching all these videos you are learning a concrete skills. Let's say you are doing B.Com right now, and you want to do become a data analyst, you can follow some tips from Hitesh here and you can make use of them. After you learn these skills it's not like someone is going to give you a job. These are the base skills which makes your foundation solid.

But after that you have to work on projects. You have to work on as many projects as you can. Now I only have a sales inside project series on my channel. I'm planning to do another project on Tableau, and I might have more projects uh on my channel in future. So if you're watching this video in the future, you will find all the useful links below. But if you don't then find try to find projects on your own, and make a solid project portfolio. After that, you need to build a solid resume. For resume also, I have done couple of uh sessions on a resume review with some experienced data analyst, and I have some data analysis resume templates as well. All the links are in video description below, and you can use those resources to build a solid resume. And then there are some tips on how to build connections on LinkedIn, etc. So try to make connections with data analysts who are already working in the industry. So when their company is hiring maybe you can use those connection to get some referral and get interview calls. So overall it will be a long process. 3 months is just to learn base skills, after that it might be many many months before you get a job. But the interesting thing is you don't have to spend much money. You just can learn these things on your own. All you need is a willpower, an internet connection and a laptop. So I hope you like this video. If you did, please give it a thumbs up! If you have any question please give it, leave a comment. I try to respond to the comments which I get in first 2 days okay? So if have question, please post a comment, I will try my best to respond. Thank you!.