MCSA Machine Learning


Machine Learning course will make you an expert in machine learning, a form of artificial intelligence that automates data analysis to enable computers to learn and adapt through experience to do specific tasks without explicit programming. You will master machine learning concepts and techniques including supervised and unsupervised learning, mathematical and heuristic aspects, and hands-on modeling to develop algorithms and prepare you for the role of Machine Learning Engineer.


In this program you will master Supervised, Unsupervised, Reinforcement, and Deep Learning fundamentals. You will also complete a capstone project in your chosen domain.

Audience


IT professionals with the following knowledge


1. Experience of publishing effective APIs for knowledge intelligence

2. Knowledge of Azure data services and machine learning

3. Familiarity with common data science processes

4. Experience withwriting and debugging R function

5. Understanding of data structures

6. Basic knowledge programming concepts

7. A high-level understanding of data platforms

Prerequisites


1. PYTHON PROGRAMMING

2. STATISTICAL KNOWLEDGE

3. CALCULUS

4. LINEAR ALGEBRA

Duration:


Total duration – 60 Hrs.

Part time - 30 days, 2hours/day.

Full time - 8 days, 8hrs/day

Key Benefits:


Exploring ,Visualizing,Processing Big Data,Managing Datasets,Preparing Data for use with Azure Machine Learning,Using Feature Engineering and Selection,Using Machine Learning with HDInsight,Using R Services with Machine Learning.

Course Outline:


70 773-analyzing big data with microsoft

  • Microsoft R Server and R Client
  • Exploring Big Data
  • Visualizing Big Data
  • Processing Big Data
  • Parallelizing Analysis Operations
  • Creating and Evaluating Regression Models
  • Creating and Evaluating Partitioning Models
  • Processing Big Data in SQL Server and Hadoop

70 774 perform cloud data science with azure machine learning

  • Introduction to Machine Learning
  • Introduction to Azure Machine Learning
  • Managing Datasets
  • Preparing Data for use with Azure Machine Learning
  • Using Feature Engineering and Selection
  • Building Azure Machine Learning Models
  • Using Classification and Clustering with Azure machine learning models
  • Using R and Python with Azure Machine Learning
  • Initializing and Optimizing Machine Learning Models
  • Using Azure Machine Learning Models
  • Using Cognitive Services
  • Using Machine Learning with HDInsight
  • Using R Services with Machine Learning

Career Prospects:


  • Machine Learning Expert
  • Data Scientist