Programming for Big Data Part I

This course builds on the theoretical knowledge gained in the Data Science course to focus on the practical applications of working with Big Data. Participants will study a variety of programming languages and work in depth with the Python language to implement a Map Reduce algorithm on a work-based data set.

Digital Skills Academy
Course Starts:
April 9, 2018
Course Ends:
May 4, 2018
Registration Closes:
April 2, 2018
4 weeks plus final assessment
Effort Per Week:
16 hours
Delivery Mode:
Data Science
Single Payment:
Total fees

Course Introduction

The course on Programming for Big Data enables participants to analyse different languages to tackle Big Data projects and solve any emerging issues in a professional and creative manner. The course addresses Programming for Big Data by providing participants with an understanding of Big Data fundamentals and gaining technical proficiency in Python, Hadoop and R as Big Data tools.

Participants will explore the Big Data environment including storage, modern databases and data warehousing. Based on the skills gained in the Data Science course, they will develop a greater understanding of typical Big Data analysis including graph and image processing, text analytics and various supervised and unsupervised predictive methodologies. Additional topics that will be covered include data visualisation and Ethics.

Impact On Upskilling Talent Pools

This course is for participants looking to gain a range of advanced skills to structure and implement programming languages for Big Data tasks and solve basic Programming for Big Data problems. This delivers particular benefits for organisations that are looking to expand data analysis skills amongst their existing talent pool. While upskilling is a vital enabler of recognition and retention for critical staff, developing Programming for Big Data talent enables firms to approach digital projects more effectively.

On completion of this course, participants will have covered:

  • How to compare and contrast the different types of Big Data
  • The analysis of a subset of the languages currently being used to solve Big Data problems
  • How to appraise a selection of Big Data algorithms and explain their usage
  • How to solve basic programming problems using Python
  • The uses of Hadoop architecture

On completion of the course, participants will have gained the following set of skills immediately applicable to their business environment:

  • Python Programming skills
  • Introduction to R programming

On completion of this course, participants will have created the following assets:

  • A variety of Python programmes
  • A selection of R programmes

Participants must have successfully completed the "Data Science" Online Short Course.

As part of our application process, participants will take a simple, online suitability assessment for their chosen course. Based on their answers, this will confirm that participants have the skills and experience required for a successful outcome.

16 hours (comprising a weekly average of 8 taught hours plus 8 additional hours on average for self-study, research and group work)

Participants will be given a number of course-specific assignments that both reinforce the learning and provide work-based experience of applying new skills. All assignments are subject to a rigorous assessment framework.

Key Benefits Of Online Short Courses

Work-Based Experience

Participants work on assignments that present work-based business challenges. They experience and meet the exacting demands of digitally-enabled change.

Collaboration Skills

Participants develop both the digital skills required by your organisation and the team-working skills needed to exploit them successfully.

Expand Your Talent Potential

The learning experience enhances the wider business skills required by your organisation. These include a digital mind-set, agile thinking and user-centred design.

Reinforcing The Learning

On Live Syncs and Mentoring sessions, participants tap into the knowledge of lecturers in real-time. They provide expert advice on assignments and support the development of group-working skills.

Flexible Learning Methodology

Digital Skills Academy short courses are based on a proven, flexible learning methodology. Content is accessible from anywhere, at any time via a computer, tablet or smartphone.

Peer Learning

Participants are part of an online international community of working professionals. So they and your organisation benefit from the insights and experiences shared by peers from across the globe.

Participant Employers

Participants represent a significant cross-section of global brands from a wide mix of industries, including the following:

Corporate Partner Feedback

“We are on the search for new skills - we are rolling out new functionality in Corporate Banking, Retail Banking, Insurance and Finance in all of the nineteen countries that we’re in. Digital Skills Academy will help significantly to fill those digital skills gaps.” Fannie Van Heerden - Head of IT Solutions, Architecture and Design, Standard Bank Group

Frequently Asked Questions

Are any additional resources needed to complete this course?

All the resources you require will be provided within this course and extra web-based resources such as official documentation will be highlighted.

How much existing knowledge of programming for big data do I require?

Participants must have successfully completed the "Data Science" Online Short Course to be eligible for this course.

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