Certified Machine Learning Expert (CMLE) Using Python - Onsite @ Singapore

“The duty of helping one’s self in the highest sense involves helping of one’s neighbours” – Samuel SmilesCASUGOLis an international certification body offering a wide-range of professional training and certification programs designed for all industries and verticals.Participants attending our programs will develop the skills and knowledge in their chosen area of professional, personal or academic interest. Programs are constantly reviewed by educators who are industry experts in their chosen field to ensure that they remain current, relevant and consistently high quality.CASUGOLstrives to be a contemporary international neighbourhood where individuals gather to learn, be inspired, share ideas, knowledge, and resources to acquire all that necessary to pursue and advance in a career of their passion. Training and certification programs are also being offered in25 CountriesincludingSingapore,Canada,France,Thailand, VietnamandMalaysiathrough our globalCertified Training Partner (CTP)network.Empowering people to be their best by making education, knowledge, and resources accessible has always been our commitment. With programs that cover a diverse range of interests, participants can certainly learn update their knowledge, gain new skills, or unleash their creativity.

CASUGOL

Acquire advanced knowledge on how to use Python Programming to apply powerful Artificial Intelligence / Machine Learning techniques

One Fullerton

For more information: www.casugol.com/cmleDuration: 4 Day / 32 HoursCertification: Participants will receive a Certificate of Competency upon successfully completing the course and passing the examination

Who Should Attend: Data Analyst, Finance Analyst, HR Analyst, System Analyst, CIO, or Anyone who is interested in pursuing a career in the areas of Artificial Intelligence / Machine Learning
Course Objective
Acquire advanced knowledge on how to use Python Programming to apply powerful Artificial Intelligence / Machine Learning techniques to gain real-world insight.

Learn how to apply Artificial Intelligence / Machine Learning techniques to analyze and organize patterns, trends, and data to make accurate real-world predictions.


Pre-Requisite
No pre-requisite. Certified Machine Learning Expert (CMLE) is suitable for everyone.


Examination
Participants are required to attempt an examination upon completion of the course. This exam tests a candidate’s knowledge and skills related to Artificial Intelligence and Machine Learning based on the syllabus covered

Participants are expected to score a minimum of 70% to pass the examinationC﻿ourse OutlineModule 1 Introduction to AI and Machine Learning
Topics Covered
<ul><li>What is Artificial Intelligence (AI)
</li><li>Concepts of machine learning
</li><li>Data and machine learning
</li><li>Real-world applications of machine learning
</li><li>How machine learning works
</li></ul>Module 2 Data Structures &amp; Managing Data Using Python
Topics Covered
<ul><li>Data and Data Types
</li><li>Deep Dive into Python
</li><li>Data Types
</li><li>Variable Operators in Python
</li><li>Data Vectors and Data Frames
</li><li>Reading and Writing Data Files to Python
</li><li>Communicating with Database via Python
</li><li>Executing SQL Using Python
</li><li>Joining Structured &amp; Semi Structured Data with Python
</li><li>Big Data Concepts &amp; Application of Python
</li></ul>Module 3 Exploring Data Using Python
Topics Covered
<ul><li>Bar Chart
</li><li>Pie Chart
</li><li>Trend Chart
</li><li>Histogram
</li><li>Box Plot
</li><li>Scattered Plot &amp; Correlation
</li><li>Other Chart
</li></ul>Module 4 Basic Classification Models &amp; Techniques
Topics Covered
<ul><li>Concept of Classification
</li><li>Supervised and Unsupervised Classification
</li><li>Decision Tree Classification
</li><li>Random Forest Classification
</li><li>Naive Bayes Classification
</li><li>Support Vector Machine
</li></ul>Module 5 Regression Methods and Forecasting
Topics Covered
<ul><li>Concept of Regression Modelling
</li><li>Modelling Stages
</li><li>Simple linear Regression
</li><li>Multiple Linear Regression
</li><li>Refining the Model
</li><li>Model Validation and Prediction
</li><li>Logistic Regression
</li></ul>Module 6 Finding Data Patterns Using Association Rules
Topics Covered
<ul><li>Concepts of Association Rules
</li><li>Market Basket Analysis (MBA)
</li><li>Support, Confidence &amp; Lift
</li><li>Other Techniques of Association
</li><li>Application of Association
</li></ul>Module 7 K-Means Clustering
Topics Covered
<ul><li>Cluster Analysis
</li><li>Hierarchical Clustering
</li><li>K-Means Clustering
</li></ul>Module 8 Evaluating and Improving Model Performance
Topics Covered
<ul><li>Model Evaluation and Comparison
</li><li>Parameters to Evaluate the Model Accuracy
</li><li>Selection of the Right Parameters for a Model
</li></ul>Module 9 Deep Dive Into Deep Learning
Topics Covered
<ul><li>Understanding the Learning Representation of Data
</li><li>Fundamentals of Deep Learning
</li><li>How Deep Learning Works
</li><li>Deep Learning and Its Application
</li><li>Future of Deep Learning
</li></ul>Certified Machine Learning Expert (CMLE) involves rigorous usage of real-time case studies, hands-on exercises, and group discussion

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Certified Machine Learning Expert (CMLE) Using Python - Onsite @ Singapore

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