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Zero To Mastery

Become an A.I. & Machine Learning Engineer

via Zero To Mastery Path

Overview

Be at the forefront of the AI revolution! This Machine Learning Engineer + AI Engineer Career Path is your step-by-step roadmap to go from beginner (at any age!) to getting hired as a Machine Learning and/or AI Engineer. You’ll be guided through our curated curriculum of courses, real-world projects, and action items to build your skills, portfolio and experience to become a top 10% Machine Learning Engineer.
  • Start with the fundamentals of machine learning including models vs. algorithms, supervised vs. unsupervised learning, and structured vs. unstructured data
  • Build neural networks using deep learning, transfer learning and more using Tensorflow and PyTorch
  • Get experience using the modern tools that big tech companies like Google, Apple, Amazon, Meta, and OpenAI use
  • Train machine learning and AI models from scratch using customized and proprietary data
  • Understand natural language processing, computer vision, convolutional neural networks and more on a deeper level
  • How to ace all of your interviews, get more job offers and a higher salary

Syllabus

  • Complete A.I. Machine Learning and Data Science: Zero to Mastery
  • Career Guide to Your Dream Job: Resumes, Interviews & Promotions
  • Apply To 5 Jobs
  • Machine Learning with Hugging Face Bootcamp: Zero to Mastery
  • The Next 2 Courses
  • PyTorch for Deep Learning Bootcamp: Zero to Mastery
  • TensorFlow for Deep Learning Bootcamp: Zero to Mastery
  • Prompt Engineering Bootcamp (Working With AI & LLMs): Zero to Mastery
  • AI Engineering: Build, Train, Fine-Tune & Deploy Models with AWS SageMaker
  • Apply To 5 Jobs You Really Want
  • Learning to Learn [Efficient Learning]
  • Statistics Bootcamp (with Python): Zero to Mastery
  • Master the Coding Interview: Data Structures + Algorithms
  • Future Proof Yourself: Goal Setting for Your Career
  • Read the Principles for Programmers
  • Take Your Next Step

Taught by

Daniel Bourke, Andrei Neagoie, Patrik Szepesi, and Scott Kerr

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