Machine Learning

IBM Introduction to Machine Learning

IBMCompleted 2024-05-13

Machine LearningEDASupervised LearningUnsupervised LearningPython

What I Learned

Understand the foundations of machine learning and the types of problems it solves

Perform exploratory data analysis and feature engineering to prepare data for modelling

Implement supervised learning algorithms including linear regression, decision trees, and SVMs

Apply unsupervised techniques such as k-means clustering and PCA for pattern discovery

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IBM Introduction to Machine Learning

IBM

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Educational Standards & Credential Integrity

This professional certificate confirms that Ankur Halder has successfully completed coursework, assessments, and technical implementations certified by IBM. Micro-credentials and formal certificates serve as verifiable evidence of mastery in modern software engineering principles, algorithms, cloud deployments, and software architecture.

Every course within this curriculum involves hands-on project building, peer code reviews, and structured knowledge evaluations designed to meet global industry requirements. The competencies gained directly enhance engineering capabilities across web development, system architecture, database optimization, and cloud operations.

To verify authentic certification status, official transcripts, and issuing authority records, use the verification link or download the signed PDF credential above. All certificates presented on this portfolio are verified through cryptographic or official issuer portals.