Data proficiency is no longer an eclectic knowledge to be limited only to a few. Instead, it is crucial to survive for everyone in any modern‐day business, regardless of which industry vertical or horizontal; whether you are a manager or a IC. And it is even required when you are starting in your career, or looking to upgrade. Data is the new gold! And not just any data, but big data since it requires some additional skillset to learn how to extract actionable insights and to solve real‐world problems.
In this jam-packed course, you will gain zero to mastery in 10 sessions. You will decipher the reality, business value, challenges and rewards of big data in order to leverage it sufficiently to advance your business goals.
You will gain an understanding of the fundamentals of data science and gain skills in programming (R, Python, Scala) and cloud machine learning tools for data science. Learn the right mix of theoretical concepts (20%), hands‐on practical exercises (70%), and business interpretation of results (10%).
By participating in this course, you will develop clarity out of the jargon and buzz words in order to make reasoned business decisions. You will be able to understand what’s feasible and what’s not – the rhetoric and realities of big data.
Develop a working knowledge of the business challenges and strategic rewards of big data initiatives that will help you as a manager. We will review real world case studies, both successful and unsuccessful ones, and the reasons for each. Learn from others' successes and failures.
We will look at different organizational structures for big data and analytics teams, and the pros and cons of each. These models will be useful for you to gain insight for your own operation. Understand the skills needed for professionals of a big data and analytics team, including what is really important to look for in a data scientist.
We understand that everyone is busy so we have given this a "boot camp" format where the emphasis is intensive hands-on technical training. You will feel empowered to utilize this knowledge in your workplace right away; you will earn the confidence necessary to make optimal decisions about the use, resourcing, risks, and value of big data.
This course, Big Data for Boot Camp, is led by Jish Nath in live/real time online through videoconferencing. See below to learn about the boot camp style format and organization of what you will learn.
“Big Data MBA” by Bill Schmarzo (ISBN 978-1-119-18111).
Big Data Boot Camp Course Outline
This curriculum has been scheduled to accommodate working professionals.
Session 1: Big Data Introduction
Session 2: Business of Big Data
Session 3: Analytics of Big Data - Part I
Session 4: Analytics of Big Data - Part II
Session 5: Big Data Technologies - Part I
Session 6: Big Data Technologies - Part II
Session 7: Big Data Technologies - Part III
Session 8: Big Data Technologies - Part IV
Session 9: Organizational Dynamics
Session 10: Future of Big Data
By the end of this course, you will:
- Acquire the skills that are needed to apply for and/or manage existing big data projects
- Gain an understanding of the business value to identify big data opportunities with maximum monetization potential
- Make reasoned assessments between risks and rewards to be able to seek support from C-level executives
- As a manager, foster better collaboration among the owners of the various big data operations
- Differentiate between what’s real and what’s not about big data when initiating an architecture discussion
- Understand the skills needed for professionals of a big data such as engineers and scientists to become a better mentor
Who Should Take this Class?
- Business and functional managers struggling to understand big data
- Executives who are trying to cut through the swirl of buzz words, technical terms, and vendor claims to make strategic decisions about big data
- Information technology managers seeking business rationalization for big data initiatives
- Analytic professionals trying to understand the differences in “regular data” and big data
- People curious about big data in order to make decisions about using it