Data Science and Machine Learning Essentials is a free online course conducted by microsoft. In this course, you will learn key concepts of data science and machine learning with examples on how to build a cloud data science solution with R, Python and Azure Machine Learning from the Cortana Analytics Suite.
About the course
Demand for Data science talent is exploding. Learn these essentials with experts from M.I.T and the industry, partnering with Microsoft to help develop your career as a data scientist. By the end of this course, you will know how to build and derive insights from data science and machine learning models. You will learn key concepts in data acquisition, preparation, exploration and visualization along with examples on how to build a cloud data science solution using Azure Machine Learning, R & Python.
What you'll learn
- The data science process
- Overview of data science theory
- Data acquisition, ingestion, sampling, quantization, cleaning and transformation
- Building data science workflows with Azure ML
- Data science tools including R, Python and SQL
- Data exploration and visualization
- Building and evaluating machine learning models
- Publishing machine learning models with the Azure ML
Course Syllabus
Module I Introduction
- Introduction to Data Science
- Overview of the Data Science process
- Introduction to Data Science technologies
- Introduction to Machine Learning
- Regressions
- Classification
- Clustering
- Recommendation
Module 2 Working with Data in Azure ML
- Data Acquisition
- Data Ingestion and Ingress
- Data Sampling and Quantization
- Data Cleaning and Transformation
Module 3: Building and Evaluation of Models
- Data Exploration and Visualization
- Business Metrics and Cost-Based Metrics
- Model Evaluation, Comparison and Selection
Module 4: Models in Azure ML, Part 1
- Regression Models
- Classification Models
- Unsupervised Learning Models
Module 5: Models in Azure ML, Part 2
- Recommendation Models
- Publishing AML Models
- Course Exam
Course Begins
- September 24, 2015
Course Length
- 5 weeks
For further information and to register, click here.