Technology & Engineering

Machine Learning Engineer

Turns data into models and models into working software, framing prediction problems, preparing datasets, training candidates and comparing them honestly on held-out data, then packaging the winner for deployment.

Level
Associate
Requirements
6
Courses
30

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Requirements

What the role asks for

Each skill is earned by completing a short list of verifying courses. Set the role as your target in the app and it orders the work for you.

  1. 01

    Computer Vision

    Computer Vision covers techniques and tools for enabling computers to interpret, analyze, and process visual data from images or videos, including tasks such as object detection, image classification, and facial recognition.

    Any 3 of 5 courses

    • Cover image for Modern Computer Vision with PyTorch
    • Cover image for Computer Vision Theory and Projects in Python for Beginners
    • Cover image for PyTorch for Deep Learning and Computer Vision
    • Cover image for Computer Vision on AWS
    • Cover image for Jetson Nano Starter to Pro - A Computer Vision Course
  2. 02

    Deep Learning Architectures & Frameworks

    Covers the design, implementation, and comparison of deep learning architectures such as CNNs, RNNs, and transformers, as well as practical use of frameworks like TensorFlow, PyTorch, and Keras for building and deploying neural networks.

    Any 3 of 5 courses

    • Cover image for Mastering PyTorch
    • Cover image for PyTorch Ultimate 2024 - From Basics to Cutting-Edge
    • Cover image for Machine Learning with PyTorch and Scikit-Learn
    • Cover image for Keras Deep Learning and Generative Adversarial Networks (GAN)
    • Cover image for Modern Deep Learning Foundations
  3. 03

    MLOps & Model Deployment

    Covers the processes, tools, and best practices for deploying, monitoring, and maintaining machine learning models in production environments, including CI/CD pipelines, model versioning, and automated retraining workflows.

    Any 3 of 5 courses

    • Cover image for Machine Learning Engineering with Python
    • Cover image for DevOps to MLOps Bootcamp: Build & Deploy ML Systems End-to-End
    • Cover image for Hands-On MLOps on Azure
    • Cover image for Practical Machine Learning on Databricks
    • Cover image for Real-world End to End Machine Learning Ops on Google Cloud
  4. 04

    Natural Language Processing

    Natural Language Processing covers techniques and tools for analyzing, interpreting, and generating human language using computational methods, including text preprocessing, sentiment analysis, language modeling, and applications in chatbots and information extraction.

    Any 3 of 5 courses

    • Cover image for Mastering NLP from Foundations to LLMs
    • Cover image for Transformers for Natural Language Processing and Computer Vision
    • Cover image for Natural Language Processing with Real-World Projects
    • Cover image for Applied Generative AI and Natural Language Processing with Python
    • Cover image for Natural Language Processing - Embeddings and Text Preprocessing in Python
  5. 05

    Statistical Analysis & Predictive Modeling

    Applies statistical techniques and machine learning algorithms to analyze data, identify trends, and build predictive models for forecasting outcomes and supporting data-driven decision-making in technology projects.

    Any 3 of 5 courses

    • Cover image for Hands-On Statistical Predictive Modeling
    • Cover image for Advanced Statistics and Data Mining for Data Science
    • Cover image for Statistics for Data Science and Business Analysis
    • Cover image for XGBoost for Regression Predictive Modeling and Time Series Analysis
    • Cover image for Regression Analysis for Statistics & Machine Learning in R
  6. 06

    Supervised & Unsupervised Learning

    Covers the principles and practical techniques of supervised and unsupervised machine learning, including model selection, training, evaluation, and clustering, with applications in data classification, pattern recognition, and predictive analytics.

    Any 3 of 5 courses

    • Cover image for Mastering Machine Learning Algorithms using Python
    • Cover image for The Complete Machine Learning Course with Python
    • Cover image for Projects in Machine Learning: From Beginner to Professional
    • Cover image for Algorithm Alchemy - Unlocking the Secrets of Machine Learning
    • Cover image for Clustering and Classification with Machine Learning in R

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