Certified Machine Learning Expert (CMLE) using ChatGPT x Python


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  • Duration: 4 Day / 32 Hours
  • Certification: 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, IT Professionals, Software Engineer, CIO, or Anyone who are interested in pursuing a career in the areas of Artificial Intelligence / Machine Learning

Course Objective

Acquire advanced knowledge on how to use ChatGPT x 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.


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


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 examination

Course Outline

Module 1
Introduction to AI and Machine Learning

Artificial Intelligence (AI) and Machine Learning (ML) are two closely related fields of computer science that focus on creating intelligent machines and developing algorithms that can learn from data and make predictions or decisions.

Topics Covered

  • What is Artificial Intelligence (AI)
  • Concepts of machine learning
  • Data and machine learning
  • Real world applications of machine learning
  • How machine learning works
  • ChatGPT and the Future of Machine Learning

Module 2
Data Structures & Managing Data Using Python

Python provides a rich set of data structures and libraries for managing and processing data. This makes it a popular choice for data science and machine learning applications. In this module, participants will gain first hand experience on the essential components required for any machine learning application.

Topics Covered

  • Data and Data Types
  • Deep Dive into Python
  • Data Types
  • Variable Operators in Python
  • Data Vectors and Data Frames
  • Reading and Writing Data Files to Python
  • Communicating with Database via Python
  • Executing SQL Using Python
  • Joining Structured & Semi Structured Data with Python
  • Big Data Concepts & Application of Python

Module 3
Exploring Data Using Python

One of the most commonly used libraries for data exploration is Pandas, which provides a high-performance data manipulation and analysis toolset. Pandas allows for easy data cleaning, merging, filtering, and grouping, and provides tools for creating visualizations such as histograms, scatterplots, and heatmaps.

Topics Covered

  • Bar Chart
  • Pie Chart
  • Trend Chart
  • Histogram
  • Box Plot
  • Scattered Plot & Correlation
  • Other Chart

Module 4
Basic Classification Models & Techniques

Python is a powerful tool for implementing basic classification models and techniques, and with the help of ChatGPT, users can get personalized guidance and support in their machine learning journey.

Topics Covered

  • Concept of Classification
  • Supervised and Unsupervised Classification
  • Decision Tree Classification
  • Deploying Classification Using ChatGPT x Python
  • Random Forest Classification
  • Naive Bayes Classification
  • Support Vector Machine

Module 5
Regression Methods and Forecasting

Scikit-learn is a popular library for regression analysis in Python, providing algorithms such as linear regression, logistic regression, and support vector regression. Together with ChatGPT, users can identify insights and best practices on data preparation, feature engineering, and performance evaluation, enabling users to build accurate and effective regression and forecasting models.

Topics Covered

  • Concept of Regression Modelling
  • Modelling Stages
  • Simple linear Regression
  • Multiple Linear Regression
  • Deploying Regression Models Using ChatGPT x Python
  • Refining the Model
  • Model Validation and Prediction
  • Logistic Regression

Module 6
Finding Data Patterns Using Association Rules

Association rule mining is a popular technique for discovering patterns and relationships in large datasets. Python provides several libraries for implementing association rule mining.

Topics Covered

  • Concepts of Association Rules
  • Market Basket Analysis (MBA)
  • Support, Confidence & Lift
  • Other Techniques of Association
  • Application of Association

Module 7
K-Means Clustering

K-Means clustering is a widely used technique in machine learning for grouping data into clusters based on similarity. In this module, participants will learn how to use Python and Chatgpt to receive personalized guidance on selecting the appropriate clustering algorithms and libraries for their specific tasks, and learn how to fine-tune the hyperparameters of the algorithms for optimal performance.

Topics Covered

  • Introduction to Unsupervised Learning Models
  • Deploying Clustering Models using ChatGPT x Python Programming
  • Cluster Analysis
  • Hierarchical Clustering
  • K-Means Clustering

Module 8
Evaluating and Improving Model Performance

Acquire knowledge on how to use Python and its libraries to Evaluate and improve model performance is a critical step in machine learning, as it helps to ensure that models are accurate and effective.

Topics Covered

  • Model Evaluation and Comparison
  • Parameters to Evaluate the Model Accuracy
  • Selection of Right Parameters for a Model

Module 9
Evaluating and Improving Model Performance

Deep learning has revolutionized the field of machine learning, enabling the development of highly accurate and complex models that can learn from large amounts of data.ChatGPT can also provide insights and best practices on data preparation, feature engineering, and evaluation metrics, enabling users to build accurate and effective deep learning models.

Topics Covered

  • Understanding Learning Representation of Data
  • Fundamentals of Deep Learning
  • How Deep Learning Works
  • Deep Learning and Its Application
  • Future of Deep Learning
  • Deep Learning in the world of ChatGPT

Certified Machine Learning Expert (CMLE) involves rigorous usage of real-time case studies, hands-on exercises and group discussion

Some Reasons Why Learners Choose CASUGOL

  • International Certification Body

  • Presence in 38 Countries

  • Developed by Industry Experts

  • More than 42,000 professionals passed through our education system

  • Flexible program design for all individuals

  • Learn from internationally renowned leading industry experts, academics, and researchers

  • Support for participants during and after training

  • Enhance competency of workforce and improve individual career prospect

  • Customization of programs for specific industry, organization, government agencies, statutory boards

  • Learn in a highly interactive, supportive and encouraging environment

  • Regular invitation to attend courses / workshops / seminars / events at complimentary rate

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Certificate Verification

All certificates issued by CASUGOL are to individuals who have successfully completed CASUGOL Certification Programs / Executive Workshops and have fulfilled all requirements by demonstrating proficiency in applying the knowledge and skills acquired.

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CASUGOL is dedicated to making education, knowledge, and resources accessible to everyone around the world. Our Financial Aid is aimed to empower learners who may encounter financial barriers in pursuit to advance their knowledge and technical know-how.

If you are unable to cover the costs of a course, you have the opportunity to request financial aid via the link found on the course's homepage. Upon approval for financial aid, you will gain full access to all course materials and can successfully complete the course to obtain a certificate.

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What Will I Receive?

If you’re approved for financial aid, you’ll receive a discount off the cost of the course. We offer financial aid to help empower learners who wouldn’t otherwise be able to afford the course fee.

In order to fairly distribute financial aid resources to the learners who need it the most, the amount of financial aid you receive may depend on the details in your application and your geographical location.

Application Status

Approved Applications

Upon approved, you will receive an email letting you know. Please follow the instructions provided in the email to begin your learning journey.

Rejected Applications

In the event that your application is declined, you will receive an email providing an explanation for the denial. If there were any issues with your initial application, you have the option to submit a new application and reapply.

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