- 6-10 weeks long
- 8-10 hours per week
- Learn for FREE, Ugpradable
- Taught by: Aneta Neumann, Katrina Falkner, Claudia Szabo, Nick Falkner, David Suter, Lewis Mitchell, Simon Tuke, Frank Neumann, Gary Glonek, Lingqiao Liu, Gavin Meredith, Ian Knight, Markus Wagner, Wanru (Kelly) Gao, Vahid Roostapour
- View Course Syllabus
Online Course Details:
Big data is changing the way businesses operate. Driven by a new scale of data collection that provides massive levels of information, businesses are now able to analyse and gather data insights to make better-informed decisions.
Data scientists and business analysts are in high-demand as companies look to use data to improve their business operations.
In this Big Data MicroMasters program, you will learn tools and analytical methods to use data for decision-making, collect and organise data at scale, and gain an understanding of how data analysis can help to inform change within organisations.
You’ll develop both the technical and computational skills that are in high demand across a range of industries. You’ll develop critical skills in programming for data science, computational thinking, algorithm design, big data fundamentals, and data-driven analysis, with plenty of opportunities to apply and explore your new learnings through a range of case studies.
- A McKinsey Global Institute study states that by 2018, the US will be facing a shortage of about 190,000 data scientists and 1.5 million managers and analysts who can understand and make decisions using Big Data. (Source: edureka!)
- A report by Glassdoor shows that the median salary for a Data Scientist is US$116,000. (Source: www.glassdoor.com)
- The average salaries for jobs with titles related to Big Data are Big Data Scientist, US$123,000, Lead Data Scientist, US$108,000, Data Scientist and Principal Data Scientist US$102,000. (Source: edureka!)
- Career prospects for people with data science skills and training include data scientist, data engineer, data architect, data administrator, data analyst, business analyst, data or analytics manager and business intelligence manager. (Source: edureka!)
What You’ll Learn:
- How to design algorithms
- Understand fundamental programming concepts including data abstraction, storage and structures
- Understand computational thinking which includes decomposition, pattern recognition and abstraction
- Data-driven problem and algorithm design for big data
- Interpretation of data representation and analysis
- Understand key mathematical concepts, including dimension reduction and Bayesian models
- How to use analytical tools such as R and Java