Certified Machine Learning Master (CMLM)
The Certified Machine Learning Master program is globally designed to develop advanced expertise in machine learning, data science, and AI-driven predictive modeling to solve complex real-world business problems.
Learn directly from global practitioners, AI and machine learning experts, and industry leaders who are shaping the future of intelligent automation, advanced analytics, and data-driven innovation.
What Sets Our Program Apart?
- Globally Recognized Certification with 2 Exam Attempts
- E-Learning Library Access, Ebook
- LinkedIn Enhancer & Professional Resume Builder
- Capstone Projects
- Generative AI Interview Practice Platform
100% Money Back Guarantee on One-Click
About Machine Learning Certification
Objectives Of Machine Learning Certification
- Validate skills in developing and deploying machine learning models.
- Master core ML algorithms for real-world applications.
- Solve industry challenges using machine learning global certification techniques.
- Streamline workflows with expert-crafted templates and resources.
- Enhance model performance through data preprocessing and feature engineering.
- Fine-tune and evaluate models for optimal results.
- Implement end-to-end machine learning pipelines.
- Master both supervised and unsupervised learning methods.
- Understand AI integration with machine learning models.
- Prepare for advanced roles in data science and AI.
Benefits Of Machine Learning Certifications
- Use expert-designed templates to accelerate machine learning projects.
- Boost your resume with a globally recognized machine learning certification exam.
- Unlock job opportunities in data science, AI, and tech.
- Solve real-world problems with machine learning solutions.
- Stand out with a certification in machine learning.
- Build employer confidence by demonstrating model deployment skills.
- Connect theory with practical machine learning applications.
- Gain access to the Generative AI Interview Practice Platform.
Exam Syllabus Of Machine Learning Certification
1 Introduction to Python Programming+
•Overview of Python
•History of Python
•Python Basics: variables, identifiers, indentation
•Python data structures (dictionary, list, string, sets, and tuples)
•Statements in Python (conditional, iterative, jump)
•OOPS concepts
•Exception Handling
•Regular Expression
2 Introduction to various packages and related functions+
•Numpy, Pandas and Matplotlib
•Pandas Module
•Series
•Data Frames
•Numpy Module
•Numpy arrays
•Numpy operations
•Matplotlib module
•Plotting information
•Bar Charts and Histogram
•Box and Whisker Plots
•Heatmap
•Scatter Plots
3 Data Wrangling using Python+
•NumPy: Arrays
•Data Operations (Selection, Append, Concat, Joins)
•Univariate Analysis
•Multivariate Analysis
•Handling Missing Values
•Handling Outliers
4 Introduction to Machine Learning with Python+
•What is Machine Learning?
•Introduction to Machine Learning
•Types of Machine Learning
•Basic Probability required for Machine Learning
•Linear Algebra required for Machine Learning
5 Supervised Learning: Regression+
•Simple Linear Regression
•Multiple Linear Regression
•Assumptions of Linear Regression
•Polynomial Regression
•R2 and RMSE
6 Supervised Learning: Classification+
•Logistic Regression
•Decision Trees
•Random Forests
•SVM
•Naïve Bayes
•Confusion Matrix
7 Dimensionality Reduction+
•PCA
•Factor Analysis
•LDA
8 Unsupervised Learning: Clustering+
•Types of Clustering
•K-means Clustering
•Agglomerative Clustering
9 Additional Performance Evaluation and Model Selection+
•AUC / ROC
•Silhouette coefficient
•Cross-Validation
•Bagging
•Boosting
•Bias v/s Variance
10 Recommendation Engines+
•Need for recommendation engines
•Types of Recommendation Engines
•Content-Based
•Collaborative Filtering
11 Association Rules Mining+
•What are Association Rules?
•Association Rule Parameters
•Apriori Algorithm
•Market Basket Analysis
12 Time Series Analysis+
•What is Time Series Analysis?
•Importance of TSA
•Understanding Time Series Data
•ARIMA analysis
13 Reinforcement Learning+
•Understanding Reinforcement Learning
•Algorithms associated with RL
•Q-Learning Model
•Introduction to Artificial Intelligence
14 Artificial Neural Networks and Introduction to Deep Learning+
•History of Neural Network
•Perceptron
•Forward Propagation
•Introduction to Deep Learning
15 Personalized Mentorship and Career Guidance+
•One-on-One Mentor Connect with Subject Matter Expert
•A dedicated 1-hour session with an experienced AI/ML practitioner
•Ask specific questions about assignments, tools, or ML algorithms
•Get feedback on your project work and coding practices
•Clarify concepts or explore certification and career planning in data science
16 Tools, Certification Prep & Real-World Projects+
•Hands-on Projects Using Real-World Datasets
•Tools Covered: Jupyter Notebook, Scikit-learn, TensorFlow (Intro), Git
•Sample Interview Questions and Capstone Guidance
•Certification Support: Python for Data Science, ML Certifications (Google, IBM, etc.)
•Real-World Case Studies in Retail, Finance, and Healthcare
•Model Deployment Concepts (Intro to Flask/Streamlite for ML Apps)
Learn from Experts
Learn from experienced practitioners and industry leaders who bring real-world expertise and practical insights to the program.
Wanda L. Curlee
AMERICAN PUBLIC UNIVERSITY SYSTEM
DEPARTMENT CHAIR
Lee Lambert
LAMBERT CONSULTING GROUP
CEO
Carsten Ley
ASIA PMO
FOUNDER, CUSTOMER
Enrollment Options
Single Access
Gain full access to our complete resource library and earn a globally recognized certification.
1 Certificate Programs
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Unlock exclusive bundle savings on premium resources and earn globally recognized credentials.
3 Certificate Programs
For Teams
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Target Audiences For Machine Learning Certification
Pre-Requisites For Machine Learning Certification
While no prior machine learning certificates are mandatory, basic programming and math knowledge are recommended to help you grasp the concepts more effectively. However, the certification exam is accessible to anyone eager to develop and validate their skills in machine learning.
Exam Details Of Machine Learning Professional (CMLP)
Exam Questions
40
Exam Format
Multiple choice
Language
English
Passing Score
65%
Duration
90 min
Open Book
No
Certification Validity
5 Years
Complimentary Retake
Yes
Sample Certification
About Machine Learning Certification
The Certified Machine Learning Master is an in-depth global certification designed for professionals who want to validate their expertise in developing, deploying, and optimizing machine learning models in real-world applications. This certification sets you apart in the competitive job market by showcasing your ability to tackle complex data challenges and drive innovation across industries.
As part of the GSDC machine learning certification, this program offers practical, hands-on experience with expert-crafted resources and ready-to-implement machine learning tools. You'll gain access to an extensive E-Learning Library, Expertly Crafted BOK (Body of Knowledge), and Capstone Projects that simulate real-world scenarios.
The Generative AI Interview Practice Platform also prepares you to confidently face interviews, making you job-ready with the knowledge and skills to solve complex problems using machine learning techniques. Earning the machine learning master certification demonstrates your proficiency in deploying machine learning models and equips you to tackle advanced roles in data science, AI, and technology sectors.