AI Engineer Associate Certificate Course (Udemy.com)
Master Machine Learning, Deep Learning & AI Agent Foundations with TensorFlow and PyTorch
Created by: School of AI
Last updated February 2026
What you will learn
- Perform advanced feature engineering for machine learning models
- Evaluate model performance using precision, recall, F1, and AUC
- Apply decision trees, random forests, and gradient boosting algorithms
- Understand deep learning concepts like activation and backpropagation
- Build neural networks from scratch using Python
- Train and deploy models using TensorFlow and Keras
- Use PyTorch to build, optimize, and evaluate deep learning models
- Understand the fundamentals of AI agents and their real-world applications
How it compares
Against the other 461 rated Udemy courses in Data Science on CourseDuck:
- Rating4.4 out of 5higher than 28% of them
- Reviews116#409 of 462 by number of reviews
- Length19.2 hourslonger than 79% of them
- Last updatedFebruary 2026more recently than 60% of them
Course Description
Take your AI skills to the next level with the AI Engineer Associate Certificate Course—a hands-on, intermediate-level program designed to help you build real-world expertise in machine learning, deep learning, and AI agent development. Whether you're an aspiring AI engineer, a data science practitioner, or a developer seeking to upskill, this course gives you a solid foundation in advanced AI techniques and the most in-demand tools like TensorFlow and PyTorch.
We begin with Feature Engineering and Model Evaluation, where you’ll learn how to prepare data for machine learning, extract meaningful features, and evaluate model performance using metrics like precision, recall, F1 score, and ROC-AUC. These skills are essential for building accurate, reliable, and production-ready ML models.
Next, we’ll cover Advanced Machine Learning Algorithms, where you'll explore real-world implementations of decision trees, random forests, gradient boosting, XGBoost, and ensemble learning. You’ll understand when and how to apply each algorithm for different data types and problem spaces.
Then we dive into Neural Networks and Deep Learning Fundamentals, giving you a clear understanding of perceptrons, activation functions, backpropagation, and network architectures. This section lays the groundwork for building your own deep learning models from scratch.
In ML Algorithms and Implementations, you'll get hands-on experience coding a variety of algorithms from the ground up. You'll sharpen your understanding of both the theory and practice behind popular ML models while reinforcing your Python programming and mathematical reasoning.
We then explore Machine Learning with TensorFlow, where you’ll build, train, and evaluate models using one of the most widely adopted deep learning frameworks in the industry. You'll learn how to construct Keras models, handle tensor operations, and work with custom training loops—essential for building scalable AI solutions.
Next up is Learning PyTorch, where you’ll experience how to use this flexible and powerful deep learning framework to implement everything from logistic regression to convolutional neural networks (CNNs). You'll understand autograd, optimizers, and how to train models in a modular, research-friendly environment.
Finally, we introduce AI Agents for Dummies, a beginner-friendly but powerful section on autonomous agents and agent-based architectures. You’ll understand the role of AI agents in decision-making, planning, and task automation, with examples from modern applications like chatbots, recommender systems, and multi-agent coordination.
By the end of the course, you’ll be able to:
Build and deploy advanced ML models
Understand the math and code behind neural networks
Use both TensorFlow and PyTorch confidently
Work with AI agent concepts and practical applications
Prepare for more specialized AI roles or certifications
Whether you're aiming to land a job as a Machine Learning Engineer, AI Developer, or simply want to deepen your understanding of artificial intelligence, this course provides everything you need to succeed.
Join thousands of learners and earn your AI Engineer Associate Certificate today—your next step toward becoming a full-stack AI engineer!
Instructor Details
- 4.4 Rating
116 Reviews
School of AI
We are your one-stop shop for all AI training needs. Since 2010, our expert instructors have been delivering top-tier education across cutting-edge technologies. Whether you’re a beginner or looking to advance your skills, our comprehensive training programs are designed to equip you with practical knowledge and real-world experience. From foundational AI concepts to advanced machine learning and deep learning techniques, we cover it all. Join us to gain hands-on expertise, guided by industry veterans committed to your success. Unlock your potential and stay ahead in the evolving world of artificial intelligence with training you can trust and results you can see.
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Reviews
By Colby Caldwell on 9/4/2026
Great match for me. Learned a lot of tensorflow and pytorch
By Ernest Manamela on 8/20/2026
It was a tough one but I gained lots of knowledge... I am going to go through it again.
By Bhakti Patel on 5/13/2026
Hard to understand when model results are not plotted on graph.
By EBINESER J on 3/25/2026
AI DEVELOPMENT AND KNOWLEDGE IMPLEMENT
By Karel Andrean on 2/10/2026
I really enjoy it how the mentor explained the materials, clear and easy to understand
By Abubakar karakkak on 9/11/2025
because the course and everything other things entails in it are good except the Use of Visual Code, which preferably Jupyter notebook or Google Colab should be used
By Ariel Beera Puoric Manyiel on 9/4/2025
The lesson is clearly explained and Hands-On exercises is straightforward.
By Alessio Vasselli on 8/22/2025
A great experience, just as Udemy has accustomed us to.
By Wilson Innocente Pita Jarawani on 7/4/2025
Very informative, credits to @jetdragacademy
By Pham Xuan Loc on 6/17/2025
An excellent course with clear, concise explanations and practical code examples
Quality Score
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Overall Score : 88 / 100












