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Hotlist of Training resources for Predictive Analytics


A hotlist of training resources for Predictive Analytics, Machine Learning, Data Science, R, Python, SAS, and Excel, including MOOCs, blogs, meetups, courses, videos, and more.



By Sameer Chopra, GVP & Chief Analytics Officer (CAO), Orbitz Worldwide

Training resources for predictive analytics? There’s an embarrassment of riches!

data-science-students

This article summarizes a list of predictive analytics education options that I’ve been aggregating — and that I recently rattled off during my participation as an expert panelist at Predictive Analytics World for Business (on June 10 in Chicago – I also delivered a keynote earlier that day). The panel topic, which seemed to greatly interest its audience, was, “Education and Training Options for Predictive Analytics.” As the session description stated, “… it’s not so easy to choose from the many educational paths available… With forecasts warning of an analytics talent shortage, a lot is at stake for this growing industry.”

Here is a list of the specific resources I had called out at the PAW panel for Advanced Analytics/ Data Science/ Big Data topics:

First some NOTES:

  • I do not list Books here;  that would be a list in itself, depending on the topic.
  • With the explosion of training platforms and vendors, this is but a small (yet highly rated/popular) subset of training avenues.  I try and point you towards free/low-cost options where I can.
  • For statistical modelers and data scientists, try not to get too caught up in the  SAS vs. R debate — learn both and you will be well positioned! Python is now table stakes too, so do strive to have all 3 in your toolbox.
  • Before getting too far down the road with data science resources, it is worth calling out that being proficient in MS Office is still also very important at the workplace.  You will stand out if you set your mind on becoming the office expert in PowerPoint and Advanced Excel!
    (chandoo.org  is a very popular resource for the latter.  I strongly encourage you to sign up for the newsletter and check out Chandoo’s tutorials on YouTube: www.youtube.com/user/ExcelTutorials)
  • I am a big believer in life-long training…would urge us all to constantly push ourselves forward with professional development and by acquiring new skills.

EDUCATIONAL RESOURCES:

MOOCS (Coursera/Udemy/edX/Udacity etc.) — Massive Open Online Courses:



KDnuggets (www.kdnuggets.com) is a must-have! It is a fantastic source for all things having to do with Analytics, Data Science, Big Data etc.  I would encourage everyone to subscribe to the daily newsletter.

Khan Academy (www.khanacademy.org) is a good educational platform.  Their bite-sized short videos on YouTube (www.youtube.com/user/khanacademy ) can be great to brush up on Analytics topics — Statistics, Probability, Linear Algebra, Calculus, Optimization etc.

YouTube (www.youtube.com) is an excellent way to get educated on pretty much any topic!
(Note: BrightTalk videos & webinars can also be a helpful educational source of Analytics in the business context. 
BrightTalk: Predictive AnalyticsBrightTalk: Big Data )

Inside BIGDATA (insidebigdata.com/category/news-analysis/ ) is great to way to stay on top of the latest happenings in Big Data Analytics!  I suggest you sign up for their free newsletter.

Predictive Analytics Times (www.predictiveanalyticsworld.com/patimes/ ) is an informative portal for Predictive Analytics.

LinkedIn Groups:  An excellent way to learn from others about Analytics topics.  You can see many of the top groups for Analytics/Data Science/Big Data/ groups in my profile (www.linkedin.com/in/choprasameer).  KDnuggets also periodically publishes trends in the top/popular Analytics groups.

CODESCHOOL (www.codeschool.com/courses) — can learn programming skills by doing. Example: Good intros for R & Python (tryr.codeschool.com/ ,    www.codeschool.com/pluralsight-courses/python-fundamentals )

DATACAMP (www.datacamp.com) — for R & Data Science.

R Resources:  Comprehensive (including books) list of 60+ R Resources: www.computerworld.com/article/2497464/business-intelligence/business-intelligence-60-r-resources-to-improve-your-data-skills.html

SAS: For those looking to get a foundation in SAS, the following set of core courses (from SAS Institute) will have you go a long way in your Analytics career:

  • Base SAS (“SAS Programming” 1/2/3)
  • SAS Statistics 1 & 2 (“Statistics 1: Introduction to ANOVA, Regression, and Logistic Regression”)
  • SAS SQL  (“SAS SQL 1: Essentials”)
  • Clustering (“Applied Clustering Techniques”)
  • SAS Macros (“SAS Macro Language 1: Essentials”)
  • Logistic Regression (“Predictive Modeling Using Logistic Regression”)
  • Enterprise Miner  (“Applied Analytics Using SAS Enterprise Miner”)

NOTE: support.sas.com/training/ has many tutorials and how-to videos. Similarly, SAS Analytics University has a comprehensive set of YouTube videos:   https://www.youtube.com/playlist?list=PLVBcK_IpFVi9cajJtRel2uBLbtcLz-WIN

Local Meetup groups (www.meetup.com) — great way to network in person and learn from others in the industry.  For instance in Silicon valley, I find The Hive to have excellent meetups for Big Data (www.meetup.com/SF-Bay-Areas-Big-Data-Think-Tank/)

Blogs/Newsletters:  A few good ones to call out here —
  1. R-Bloggers (www.r-bloggers.com/)
  2. KDnuggets (www.kdnuggets.com/)
  3. Analytics Vidhya (www.analyticsvidhya.com/ )

KAGGLE (www.kaggle.com) — for education by doing, a great way to jump into the weeds with trying your hand at a public challenge/competition for data scientists.

University Degree Programs in Data Science — see www.mastersindatascience.org/ for a complete and up-to-date list of Masters programs in Data Science. www.mastersindatascience.org/schools/data-science-degrees-online/ has the list for Data Science degrees online programs.

(Note: KDnuggets periodically also publishes a similar list.  This one is from 2014 for online degrees in Analytics/Data Science www.kdnuggets.com/2014/07/online-degrees-analytics-data-mining-data-science.html)



Hope this was helpful.  I welcome any comments/feedback: LinkedIn: www.linkedin.com/in/choprasameer Email:  sameer.chopra@orbitz.com Twitter: @sameerchopra99

Originally published in Predictive Analytics Times. Reposted by permission.

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