Training Level

Intermediate

Training Duration (Days)

6

Training Mode

  1. Physical classroom
  2. Online

Prerequisite

  1. Programming fundamentals
  2. Core Python syntax
  3. Basic statistics

Career Track

Data Scientist

Industry Skill
Framework

Accreditation Body

N/A

Skill Outcome

By the end of this course, you will be able to:

  1. Knowledge of hypothesis forming and testing
  2. Curation of relevant data using visualisations that assists stakeholders’ understanding
  3. Explore and analyse data for insights using visualisation
  4. Explain insights with clear and compelling written, verbal and visual communication
  5. Extraction of knowledge and insights generation
  6. Map data sources to data visualisation libraries
  7. Ability to write code to read data, access packages, apply logic Debugging, profiling and optimization
  8. Ability to clean data through statistical approaches, such as identifying outliers Ability to transform data into machine-readable formats
  9. Create, read, update and delete on databases and apply data normalisation
  10. Deep knowledge of statistical and mathematical concepts Identify trends and behaviours with descriptive statistics
  11. Knowledge of common models for prediction such as linear and logistic regression
  12. Ability to research latest methods to improve the accuracy and results Knowledge of big data tools and platforms to access data and run models
  13. Ability to manage the deployment of model lifecycles Identify, monitor, and measure quality of models over time
  14. Data Governance
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