Course Code: datsci7
Duration: 245 hours
Prerequisites:

Participants to have good grounding in maths, at least high school level.

Though programming skills are not required, any programming skills will be useful.

Participants will be assessed and interviewed prior to participation in this training programme.

Overview:

The explosion of information and data in today’s world is un-paralleled, our ability to innovate and push the boundaries of the possible is growing faster than it ever has. The role of Data Scientist is one of the highest in-demand skills across industry today.

We offer much more than learning through theory; we deliver practical, marketable skills that bridge the gap between the world of academia and the demands of industry.

This 7 week curriculum  can be tailored to your specific Industry requirements, please contact us for further information or visit the Nobleprog Institute website 

Audience:

This programme is aimed post level graduates as well as anyone with the required pre-requisite skills which will be determined by an assessment and interview. 

Delivery:

Delivery of the course will be a mixture of Instructor Led Classroom and Instructor Led Online; typically the 1st week will be 'classroom led', weeks 2 - 6 'virtual classroom' and week 7  back to 'classroom led'. 

Course Outline:

Week 1 Big Data concepts

  • VVVV (Velocity, Volume, Variety, Veracity) definition
  • Limits to traditional data processing capacity
  • Distributed Processing
  • Statistical Analysis
  • Machine Learning Analysis Types
  • Data Visualization
  • Distributed Processing (e.g. map-reduce)
  • Introduction to used languages
  • R language crash-course
  • Python crash course

Weeks 2&3 Performing Data Analysis

  • Statistical Analysis
  • Descriptive Statistics in Big Data sets (e.g. calculating mean)
  • Inferential Statistics (estimating)
  • Forecasting with Correlation and Regression models
  • Time Series analysis
  • Basics of Machine Learning
  • Supervised vs unsupervised learning
  • Classification and clustering
  • Estimating cost of specific methods
  • Filter

Week 4 Natural Language Processing

  • Processing text
  • Understanding meaning of the text
  • Automatic text generation
  • Sentiment/Topic Analysis
  • Computer Vision

Week 5&6 Tooling concept

  • Data storage solution (SQL, NoSQL, hierarchical, object oriented, document oriented)
  • MySQL, Cassandra, MongoDB, Elasticsearch, HDFS, etc...)
  • Choosing right solution to the problem
  • Distributed Processing
  • Spark
  • Machine Learning with Spark (MLLib)
  • Spark SQL
  • Scalability
  • Public cloud (AWS, Google, etc...)
  • Private cloud (OpenStack, cloud foundry)
  • Autoscalability

Week 7 Soft Skills

  • Advisory & Leadership Skills
  • Making an impact: data-driven story telling
  • Understanding your audience
  • Effective data presentation - getting your message across
  • Influence effectiveness and change leadership
  • Handling difficult situations

Exam

  • End of Programme graduation exam
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