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Learning path & resources to start your data science (analytics) career today

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Marie said it correctly – the most difficult step in any process is the first step!Start your analytics career today

 

Recently, we launched a list of various analytics trainings being offered across the globe and are still adding more trainings to it to make it more comprehensive. While we get the entire page up and ready for you, I thought let me start putting down ways in which this information would be helpful to people.

What better place to start, than to help out the people who need it the most? Yes you are right…I am talking about people who want to start their journey in analytics or are in very initial stages of doing so. For the purpose of this article, I’ll also assume that you are motivated to take this journey in self learning mode. If you are not or need higher degree of assistance, you can easily go back to the listing page and substitute these resources for paid ones based on their ratings and subject matter.

These resources should make you knowledge ready for your first job in analytics industry

Analytics and Big Data Salary Report

 

Choice of Language:.

I strongly believe that the choice of your first language should be a mainstream one! It helps you get a lot of resources and large community / tech support to fall back upon. For this reason, you should either choose R or SAS. You can also think of Python, WEKA or Matlab, but I would suggest R or SAS over them. Between R & SAS, you can not go much wrong – SAS has the biggest market share and R is catching up fast. Both offer free versions for learning, which you can download for learning the software. If you are still confused about the choice, you can read a detailed comparison here.

 

Books to read:

To understand power of analytics:

These books provide a good overview of how analytics can impact our business decisions and thought process, challenges faced in implementing data based solutions and also its limitations (the last one).

Freakonomics by Steven D. Levitt

Moneyball by Michael Lewis

Scoring points by Clive Humby and Terry Hunt

When Genius Failed by Roger Lowenstein

 

Gearing up on the subject:

The Signal and the Noise by Nate Silver

Big Data – A revolution that will transform How we live, work and think

Web Analytics 2.0 by Avinash Kaushik

 

Video based trainings:

Learning the basics:

Linear Algebra and Statistics from Khan Academy – All the basics you would need explained in awesome way! You realize how learning can be fun when you see them for the first time

Intro to Descriptive Statistics on Udacity & Inferential Statistics on Udacity – for the activity filled classes and exercises they provide.

 

For learning tools

Base SAS and Statistics course from SAS Institute – If you choice of tool is SAS

SAS Analytics U tutorials from SAS Institute (again if SAS is your choice)

Data Science Specialization from John Hopkins University on Coursera – If you want to take learning in relaxed manner (3 – 4 hours every week over a period on 9 months)

edX Analytics Edge (R) – For those who can sustain more intensive schedule (20 – 25 hours every week for 3 months)

Google Analytics certification by Google – if you want to build a career in Web Analytics

Chandoo.org for learning and refreshing Excel – it contains some nice tips and tricks.

Qlikview / Tableau Tutorial – I think you should learn one of these visualization tools, so that you can draw powerful visualizations quickly

 

Other Reference material:

SAS Analytics U – download center

SAS documentation & SUGI papers

CRAN project website for downloading R and packages

Videos from Google on R (available on YouTube)

R documentation

 

For staying up to date with the industry

Subscribe to following blogs;

 

Do you think I have missed out on any resources, which can be immensely valuable to a newbie in this industry? If so, please feel free to add them here.

If you like what you just read & want to continue your analytics learningsubscribe to our emailsfollow us on twitter or like our facebook page.

18 Comments

  • Tejasvi says:

    Hey! Kunal,

    Thank you for compiling all the pertinent data. It is almost exhaustible for someone, like me, who is starting a career in Analytics.

    Looking forward to more insights from and for the industry.

  • Mayank Patel says:

    Hi Kunal,

    Great articles (all over the website) Kunal.
    I had some queries.
    I am a software tester in an MNC for about 20 months and have done testing on data and reports processed and developed using MSBI (SSIS, SSRS, SharePoint services).
    I want to learn data analytics (as i want to do MS in MIS in future) and am researching for the same.
    Initially i wanted to start with R as its a programming language and i would learn from scratch but as i read your article comparing R vs Python vs SAS, i thought SAS was a good option for me to start.
    I browsed through the net and found that i can start with SAS Base Programmer 9.0 certification, for this SAS offers SAS Prep guide (worth 9K 🙁 ) but also the reviews on the net say “Its not the best but its the only source”.

    Questions:
    1. Am i correct in starting with SAS over R considering my future ambition ?
    2. Do you know any other good sources for learning for SAS ?

    Thanks in advance bro 🙂

    • Kunal Jain says:

      Mayank,

      As I said, there is no right or wrong answer between R and SAS. It is just the fit in various scenarios.

      SAS has far bigger market share in India, but is more expensive – so most of the new startups rely on R and not SAS. If you want base SAS certification – the free course on SAS website should besufficient.

      Regards,
      Kunal

  • Siddharth Sharma says:

    Hi Kunal.

    Excellent Article to help the Beginners.

    Thanks,
    Siddharth Sharma

    • Gautam Anand says:

      Hi Kunal

      You have started a very good effort for the beginners. Its very nice to read the articles by you and your team. I am learning a lot by visiting here.
      Its also good to see Sid (My senior Mr. Sidhartha Sharma) visiting here 🙂

  • Mohan says:

    Thanks Kunal for putting all the learning’s at one place. 🙂

  • Akif Fırat Şentaş says:

    Hi,

    I also find your article very helpful. Thank you for that. I want to decide which program i am going to focus on.
    I figured something that in your final scorecard both the total and average points of Python and SAS are the same and R is the highest one. When i tried to break the equivalence with some factors, R is still on top.

    So i would like to ask you about one other criteria if i may;
    As far as i know R needs installment of the relevant packages every time which you have to use during process and this might be hard time to time.
    What about ease of use after learning? What would be your points for these three programmes?

    Thanks for your time.

    • Kunal Jain says:

      I personally think that installing a library is not that big a problem – bot R and Python rely on this architecture. But, over time you will realize that bulk of your work actually happens through a limited set of libraries. Also, installing them is easy – so I wouldn’t say that it is difficult to use.

      SAS will provide most of the procs you need in the base SAS – but will charge you heavily for any additional procs you need (for example creating a decision tree) or additional things you might need.

  • Santosh says:

    Dear Kunal,

    The article was most comprehensive & enabling. Helps us starters make informed decisions. I have a few more specific questions on these lines.

    I hold a master’s degree in marketing & bachelor’s degree in commerce. I have been working for 2.5 years now in a top 5 India based IT MNC. I have always had a huge passion for sales. Now, I also have a big crush on Analytics, especially on topics like BA, BI, decision sciences etc. 2-3 years from now,

    I want to land up in a Analytics sales/consulting role.

    So here are my questions –
    1. How do you think i should go about it? Will a course be the right launchpad? If yes, which one (most of them seem to be technical & aimed at creating data scientists)??
    2. How important is it to learn a tool (SAS/R/Python) for career of this sort?
    3. Apart from a course, staying abreast about industry trends etc. what are the other things you would prescribe to build a successful Analytics sales/consulting career?

    Many thanks in advance for the time & patience you will have put to read through and answer my questions.

    Regards & patronage,
    Santosh Sridhar

    • Kunal Jain says:

      Santosh,

      1. Santosh, I think the course from Great Lakes can be a good start – their focus is to enable you with understanding about analytics rather than creating a data scientist. I have done a detailed review of this programme recently – you can have a look at it here.

      2. I think you should have a good understanding of what each tool does, their benefits and down-sides. That should be good enough to get you started. What is more important is similar understanding of techniques in various domains – for example – which algorithm can help predict the next product sales to the customers of Walmart?

      3. You should focus on gaining breadth over depth – for this kind of path. Read, read and read a lot – subscribe to various blogs (including Analytics Vidhya) like KDNuggets, smartdatacollective, big data made simple. You can rely on news aggregators like Prismatic to provide you with latest news in the industry.

      Hope this helps.

      Regards,
      Kunal

  • Mukul Singh says:

    Hi kunal,

    I am a b.com graduate and carry an experience of 5 years with genpact in training, operations and handled lil part of data reporting in analytics domain. Currently I am in educatfikon industry mentoring students on CA and CS course. I wish to switch in analytics. I am good at advanced excel and know some part of excel VBA.

    Please suggest what necessary steps should be taken to get into this. Someone suggested me to enrolled in jigsaw online course as I am based out of jaipur.

    Please suggest. Thanks in advance.

    • Kunal Jain says:

      Hi Mukul,

      If you have resources, I would suggest to try for the Certificate programme in business analytics from Indian School of Business in Hyderabad. ISB is one of the best course available in India as of now. If you want to move into Business analytics, this might be the best chance. This is an offline part-time course though.

      But If you want to join a short term online course – Foundation course in Analytics of Jigsaw academy is a good option for you to pursue in Analytics.

      Regards,
      Kunal

  • Anshuman Singh says:

    Brilliant compilation ! Thanks a ton.

  • Rakesh Jha says:

    Hi Kunal

    Nice article. I am currently at beginner’s level in the analytics industry and have some knowledge of SAS, SQL and statistics. I would like to focus more on predictive analytics for advancing my career.

    Do you know of any good courses in this area?

    Thanks
    Rakesh

  • C. Santos says:

    Hi Kunal,

    Thanks a lot for your article! Being a data analyst rookie myself, I have found invaluable piece of advice with your help. Also, I wanted to touch base with you regarding kaggle.com. I have recently heard about it and, noticing it is not listed, I was wondering what are your thoughts about this platform.

    Regards,
    C. Santos

  • Kishan Majumder says:

    Dear kunal
    Could you please tell me that is it good to join a company like Musigma to start a career in analytics……..

  • Lalatendu Das says:

    Hi Kunal,
    First off Analytic Vidhya’s work on this field is excellent. Hat’s off to your team.
    I have one confusion here, Earlier as part of another blog you have segregated the work in Analytic field in 3 sections and like Data scientist, Data engineer and Statistician, So the path you described here is apt for the 1st category only. Am I right here. ? Or this is a overlapping step and applicable for all the role types. For gaining fair level of knowledge and able to work as a Data engineer Is the above steps are must.?

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