Training Resources

icon_EducationWelcome to the Women in Big Data Training Page!

Here you will find information on all of our past and upcoming technical and non-technical training workshops. We are still building up a list of future topics and dates so please check back here periodically for our quarterly events. Ideally, we would develop the list of upcoming topics from your input, Here is a link to a super-brief survey where you can influence future training content.

Thank you in advance for letting us know what kind of training would help you progress on your Big Data path.

Women in Big Data Training Committee

Intel Nervana AI A Academy

Data Science is an ocean of information–stay focused!
How do I become a good data scientist? Should I learn R* or Python*? Or both? Do I need to get a PhD? Do I need to take tons of math classes? What soft skills do I need to become successful? What about project management experience? What skills are transferable? Where do I start?
Click here to view a primer from Intel on how to become a data scientist. Training

Boost your career with online courses taught by industry experts. Courses are available on a range of topics, including  computer science, economics, statistics, math and more. Languages, including Python and R, are taught in classes starting at the beginner level (knowledge of basic statistics recommended).

Special offer for Women in Big Data Forum members:

Big Data University

Analytics, Big Data, and Data Science Courses.
Your awesome career in Data Science and Data Engineering starts here.

Click here to learn more, view the courses, and sign up.

Complimentary Online Training Courses by Linux Foundation for Q317

The Women in Big Data Forum, in partnership with the Linux foundation, is giving out limited complimentary codes for the following courses:

  • Essentials of System Administration
  • Linux Networking and Administration
  • Linux Security Fundamentals
  • Cloud Foundry for Developers
  • Containers for Developers and Quality Assurance
  • Kubernetes Fundamentals
  • Software Defined Networking Fundamentals
  • Fundamentals of Professional Open Source Management

Check out these courses here.

Deadline to register using the complimentary code is September 30, 2017.

If you are interested to get a code to register for a course, please contact (Note: one code is goof for one course only. Codes are valid only courses only (not valid on course + certification bundle).

Happy learning.

Omidyar Network Learning Series: What is Big Data, Small Credit?
This learning series explores an innovative business model that leverages big data to help consumers who are invisible to lenders to gain access to credit. Find out how Big Data, Small Credit can help consumers to improve their lives, financial service providers to open new markets, and emerging markets to bolster their economies. Click here to check it out.


February 2016 Apache Hadoop Training

Learning and Networking: Cloudera Essentials for Apache Hadoop
On February 29th, 40 Women in Big Data and their supporters attended a day long training hosted by Cloudera titled, ‘Learning and Networking: Cloudera Essentials for Apache Hadoop’.  Attendees learned how Apache Hadoop addresses the limitations of traditional computing, helps businesses overcome real challenges, and powers new types of big data analytics. This series also introduced the rest of the Apache Hadoop ecosystem and outlines how to prepare the data center and manage Hadoop in production. If you missed it, please refer to these training videos.

Spark SQL Training Session: Course Materials & Recording Now Available

Materials from August 2016 meetup can be downloaded from:

Gayathri’s slides on Spark Overview and Spark Data Sources:

Xinh’s slides on Spark SQL:

Recording of the training:

Defining Machine Learning
Wikipedia Defines Machine Learning

Review details.

eBay Technology
Here are links dealing with the internal workings of eBay’s search engine, data, and architecture.

Intel® Nervana™ AI Academy

NVIDIA Deep Learning Institute
Hands-on training for developers, data scientists, and researchers

Review details.

Deep Learning by Google
Take Machine Learning to the Next Level

Review details.

Microsoft Deep Learning Group:
Advancing the state-of-the art in deep learning to achieve general intelligence

Review details.

Machine Learning
Stanford University, Andrew Ng

This course provides a broad introduction to machine learning and statistical pattern recognition. Topics include: supervised learning (generative/discriminative learning, parametric/non-parametric learning, neural networks, support vector machines); unsupervised learning (clustering, dimensionality reduction, kernel methods); learning theory (bias/variance tradeoffs; VC theory; large margins); reinforcement learning and adaptive control. The course will also discuss recent applications of machine learning, such as to robotic control, data mining, autonomous navigation, bioinformatics, speech recognition, and text and web data processing.

Deep Learning Tutorial
Stanford University

Review details.