Programming for Big Data Part II

This course builds on the theoretical knowledge gained in the Data Science and the Programming for Big Data Part I courses and prepares participants to manage and solve advanced Big Data problems in a hands-on digital business environment.

Certification:
Digital Skills Academy
Course Starts:
May 14, 2018
Course Ends:
June 15, 2018
Registration Closes:
May 7, 2018
Duration:
5 weeks plus final assessment
Effort Per Week:
15 hours
Delivery Mode:
Online
Category:
Data Science
Fees:
Single Payment:
Total fees

Course Introduction

The course addresses advanced features and techniques of the Python language to help participants identify and solve intermediate programming problems. Participants will first do an in-depth examination of the Python language and analyse a work-based Big Data problem. They will need to select an appropriate methodology to solve the identified issue and implement the relevant design in the Python language.

Participants will also gain a high-level understanding of Map Reduce, Graph Databases and Data Visualisation and develop their critical thinking and problem-solving skills.

Impact On Upskilling Talent Pools

This course is for participants looking to gain advanced technical and problem-solving skills in the field of Big Data Programming. This delivers particular benefits for organisations that are looking to expand data analysis skills and build an expert talent pool in this specialist field. While upskilling is a vital enabler of recognition and retention for critical staff, developing expert talent in the field of Big Data and Programming enables firms to launch highly technical digital projects.

On completion of this course, participants will have covered:

  • How to work with Python to solve intermediate programming problems
  • The use and benefits of Map Reduce
  • How to work with Graph Databases
  • How to work with Python to implement a selection of standard Big Data algorithms
  • Aspects of data visualisation and how to prepare data for visualisation

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" and "Programming for Big Data Part I" Online Short Courses, to be eligible for this 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.

15 hours (comprising a weekly average of 7.5 taught hours plus 7.5 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. Specific assessments for this course include a weekly quiz and one major assignment covering a programming challenge in Python.

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" and "Programming for Big Data Part I" Online Short Courses, to be eligible for this course.

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