&lt;p&gt;Certificate in Machine Learning Associate is an international certification offered to professionals engaged in Machine Learning. Sponsored by Logical Operations, a globally recognized certification and training provider based in the US, Certificate in Machine Learning Associate addresses the dynamic requirements of the machine learning field. The Certificate in Machine Learning Associate designation certifies professionals who have effectively demonstrated their expertise in machine learning concepts, algorithms, and applications.&amp;nbsp;&lt;&#x2F;p&gt;

Certificate in Machine Learning Associate is an international certification offered to professionals engaged in Machine Learning.

<ul><li class="ql-align-justify">Definitions and core concepts of machine learning&nbsp;</li><li class="ql-align-justify">Evolution and impact of machine learning&nbsp;</li><li class="ql-align-justify">Key applications and case studies&nbsp;</li><li class="ql-align-justify">Overview of common machine learning tools and platforms&nbsp;</li></ul>

Introduction to Machine Learning

<ul><li class="ql-align-justify">Overview of supervised learning&nbsp;</li><li class="ql-align-justify">Algorithms: Linear Regression, Logistic Regression, Decision Trees, Support Vector Machines&nbsp;</li><li class="ql-align-justify">Model evaluation metrics: Accuracy, Precision, Recall, F1 Score&nbsp;</li><li class="ql-align-justify">Case study: Application in financial forecasting&nbsp;</li></ul><p><br></p>

Supervised Learning Techniques

<ul><li class="ql-align-justify">Introduction to clustering and association algorithms&nbsp;</li><li class="ql-align-justify">Algorithms: K-Means, Hierarchical Clustering, Apriori algorithm&nbsp;</li><li class="ql-align-justify">Techniques for dimensionality reduction: PCA, t-SNE&nbsp;</li><li class="ql-align-justify">Case study: Market segmentation using clustering&nbsp;</li></ul>

Unsupervised Learning Techniques

<ul><li class="ql-align-justify">Basics of neural networks and the architecture of deep learning&nbsp;</li><li class="ql-align-justify">Deep learning frameworks: TensorFlow, Keras&nbsp;</li><li class="ql-align-justify">Applications: Image recognition, Natural Language Processing&nbsp;</li><li class="ql-align-justify">Practical exercise: Building a simple neural network&nbsp;</li></ul>

Neural Networks and Deep Learning

<ul><li class="ql-align-justify">Data collection and cleaning techniques&nbsp;</li><li class="ql-align-justify">Feature selection and feature engineering methods&nbsp;</li><li class="ql-align-justify">Handling imbalanced data&nbsp;</li><li class="ql-align-justify">Practical session: Preparing data for a machine learning model&nbsp;</li></ul>

Data Preparation and Feature Engineering

<ul><li class="ql-align-justify">Techniques for deploying machine learning models&nbsp;</li><li class="ql-align-justify">Introduction to model monitoring and maintenance&nbsp;</li><li class="ql-align-justify">Use of A/B testing frameworks&nbsp;</li><li class="ql-align-justify">Discussion on ethical considerations in machine learning&nbsp;</li></ul>

Model Deployment and Monitoring

<ul><li class="ql-align-justify">Participants are divided into groups&nbsp;</li><li class="ql-align-justify">Each group develops a machine learning project from conception to deployment&nbsp;</li><li class="ql-align-justify">Application of theory in real-world scenarios&nbsp;</li><li class="ql-align-justify">Group presentations and project evaluation&nbsp;</li></ul>

Real-world Machine Learning Project Simulation

<ul><li class="ql-align-justify">Assessment of projects by instructors and peers&nbsp;</li><li class="ql-align-justify">Individual and group reflections on learning outcomes&nbsp;</li><li class="ql-align-justify">Final exam&nbsp;</li></ul>

Certificate in Machine Learning Associate (CMLA)

Examination

Program Objectives

Program Modules

Enhance Your Academic Journey with Us!

Certificate in Machine Learning Associate (CMLA)

Examination

Program Objectives

Program Modules

02Supervised Learning Techniques

03Unsupervised Learning Techniques

04Neural Networks and Deep Learning

05Data Preparation and Feature Engineering

06Model Deployment and Monitoring

07Real-world Machine Learning Project Simulation

08Evaluation and Reflection

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Enhance Your Academic Journey with Us!