What will you learn in Machine Learning with Mahout Certification Training Course
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Grasp the architecture and core components of Apache Mahout on Hadoop.
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Implement scalable machine learning algorithms for clustering, classification, and recommendation.
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Perform data preprocessing and feature engineering at scale.
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Build collaborative-filtering and content-based recommendation engines.
Program Overview
Module 1: Introduction to Apache Mahout
⏳ 1 hour
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Topics: Mahout history, ecosystem, core libraries, and use cases.
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Hands-on: Explore the Mahout shell and sample datasets.
Module 2: Environment Setup & Data Ingestion
⏳ 1.5 hours
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Topics: Hadoop cluster basics, Mahout installation, HDFS operations.
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Hands-on: Configure Mahout on a local Hadoop setup and ingest CSV data.
Module 3: Data Preprocessing & Feature Engineering
⏳ 2 hours
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Topics: Text vectorization, normalization, handling sparse data.
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Hands-on: Convert raw logs or text into Mahout’s vector formats.
Module 4: Collaborative Filtering
⏳ 2 hours
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Topics: User-based vs. item-based filtering, similarity measures.
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Hands-on: Build and evaluate a recommendation engine on a movie dataset.
Module 5: Classification with Naive Bayes & Random Forest
⏳ 2.5 hours
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Topics: Probabilistic classifiers, decision forests, model evaluation.
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Hands-on: Train and test classifiers on a large, labeled dataset.
Module 6: Clustering with K-Means & Canopy
⏳ 2 hours
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Topics: K-means algorithm, canopy clustering, choosing k.
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Hands-on: Cluster product or user data and visualize cluster assignments.
Module 7: Custom Algorithm Implementation
⏳ 1.5 hours
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Topics: Writing custom Mahout jobs, extending the API.
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Hands-on: Implement a small custom mapper/reducer for a bespoke algorithm.
Module 8: Deployment & Optimization
⏳ 1.5 hours
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Topics: Job tuning, resource management, monitoring Mahout jobs.
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Hands-on: Deploy a fully working recommendation pipeline in Hadoop YARN.
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Job Outlook
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Big data and machine learning roles increasingly demand scalable algorithm expertise.
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Apache Mahout skills are valued for building production-grade recommendation systems and clustering pipelines.
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Typical roles include Big Data Engineer, ML Engineer, and Data Scientist with Hadoop focus.
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Salaries range from $100K–$140K USD, with high demand in e-commerce and media streaming sectors.
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