Data Science and Machine Learning (SF)
About This Course
1. Understand fundamentals of Data Science and Machine Learning
2. Create Simple Machine Learning Implementation in Cloud
3. Implement Data Science using R
4. Build Machine Learning using R packages
5. Implement Data Science using Python
6. Build Machine Learning using Python packages
What You'll Learn
Module 2: Managing Datasets using Azure Machine Learning - Regression
Module 3: Managing Datasets using Azure Machine Learning- Classification
Module 4: Building product recommendation Machine Learning System
Module 5: Introduction to R and R Studio
Module 6: Variable types and data structures
Module 7: Base graphics system in R
Module 8: General linear regression in R
Module 9: Introduction to Python for Data Science
Module 10: Data Processing with Numpy and Pandas
Module 11: Data Visualization with Matplotlib
Module 12 : Machine Learning with Scikit Learn
Entry Requirements
Demographics:
• Age: Minimum 18 years old.
Education:
• Minimum GCE ‘O’ Level.
• Language: Workplace Literacy and Numeracy Level 5 (WPLN: Speaking, Writing, Listening, Reading, and Numeracy at ESS level 5 or equivalent to Upper Secondary Level of English and Mathematics).
Technical Skills and Knowledge
Before attending this course, students must have the following technical knowledge:
• Some knowledge in programming languages, such as: Java, C#, or any other high-level programming language.
• Related working experience in business intelligence.
• Basic knowledge in application or software development methodologies.
Working Experience
• Recommended to have at least 1 year working experience in BI (Business Intelligence) or software development.