Certified Machine Learning Specialist
 /  Certified Machine Learning Specialist

A Certified Machine Learning Specialist understands how and where machine learning and deep learning technology and techniques are best utilized to produce business value. Machine learning algorithms and system design principles are of second nature to the Certified Machine Learning Specialist, who further possesses in-depth knowledge of deep learning techniques, as well as supervised, semisupervised and unsupervised machine learning processing models and approaches. A Certified Machine Learning Specialist further has an understanding of how machine learning relates to and can be utilized together with data science and artificial intelligence.

Module 1: Fundamental Machine Learning

This course provides an easy-to-understand overview of machine learning for anyone
interested in how it works, what it can and cannot do and how it is commonly utilized
in support of business goals. The course covers common algorithm types and further
explains how machine learning systems work behind the scenes. The base course
materials are accompanied with an informational supplement covering a range of
common algorithms and practices.
The primary topics covered by this course are:
• Machine Learning Business and Technology Drivers
• Machine Learning Benefits and Challenges
• Machine Learning Usage Scenarios
• Datasets, Structured, Unstructured and Semi-Structured Data
• Models, Algorithms, Model Training and Learning
• How Machine Learning Works
• Collecting and Pre-Processing Training Data
• Algorithm and Model Selection
• Training Models and Deploy Trained Models
• Machine Learning Algorithms and Practices
• Supervised Learning, Classification, Decision Tree
• Regression, Ensemble Methods, Dimension Reduction
• Unsupervised Learning and Clustering
• Semi-Supervised and Reinforcement Learning
• Machine Learning Best Practices
• How Machine Learning Systems Work
• Common Machine Learning Mechanisms
• How Mechanisms Are Used in Model Training
• Machine Learning and Deep Learning, Artificial Intelligence (AI)Advanced Machine Learning

Module 2: Advanced Machine Learning

This course delves into the many algorithms, methods and models of contemporary
machine learning practices to explore how a range of different business problems can
be solved by utilizing and combining proven machine learning techniques.
The following primary topics are covered:
• Data Exploration Patterns
• Central Tendency Computation, Variability Computation
• Associativity Computation, Graphical Summary Computation
• Data Reduction Patterns
• Feature Selection, Feature Extraction
• Data Wrangling Patterns
• Feature Imputation, Feature Encoding
• Feature Discretization, Feature Standardization
• Supervised Learning Patterns
• Numerical Prediction, Category Prediction
• Unsupervised Learning Patterns
• Category Discovery, Pattern Discovery
• Model Evaluation Patterns, Baseline Modeling
• Training Performance Evaluation, Prediction Performance Evaluation
• Model Optimization Patterns
• Ensemble Learning, Frequent Model Retraining
• Lightweight Model Implementation, Incremental Model Learning

Module 3: Machine Learning Lab

This course module presents participants with a series of exercises and problems that
are designed to test their ability to apply their knowledge of topics covered in previous
courses. Completing this lab will help highlight areas that require further attention and
will further prove proficiency in machine learning systems and techniques, as they are
applied and combined to solve real-world problems.
For instructor-led delivery of this lab course, the Certified Trainer works closely with
participants to ensure that all exercises are carried out completely and accurately.
Attendees can voluntarily have exercises reviewed and graded as part of the class
completion. For individual completion of this course as part of a study kit, a number
of supplements are provided to help participants carry out exercises with guidance.

This course is targeted for the following audience:

• Analytics Managers

• Business Analysts

• Information Architects

• Developers looking to become Data Scientists

• Individuals seeking a career in Machine Learning.

To achieve this certification, Exam ML90.01 must be completed with a passing grade. For more information on exam format / preparation / policies, visit https://www.arcitura.com/next-gen-it-academy/exams/exam-ml90-01-machine-learning-specialist/

  • 13 – 15 Jan 2020
  • 4 – 6 May 2020
  • 21 – 23 Sep 2020
  • 23 – 25 Nov 2020

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Course Fee $3,500.00
Course Fee after GST $3,745.00
Certification Body
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