Overview
Build deep learning models from scratch using PyTorch with a strong engineering foundation, Build deep learning models from scratch using PyTorch with a strong engineering foundation, Understand and apply neural networks, backpropagation, and optimization effectively, Train, evaluate, and improve models using regularization and generalization techniques
Machine learning engineers who want to deepen their understanding of deep neural networks, Software engineers transitioning into AI and deep learning roles, Data scientists looking to build production-ready deep learning models, Students and graduates preparing for AI, ML, or deep learning interviews
Build CNNs and sequence models for real-world vision and time-series tasks., Build CNNs and sequence models for real-world vision and time-series tasks., Apply CNNs and sequence models to solve real image and time-series problems end-to-end., Create computer vision and time-series solutions using CNNs and sequence networks.
“This course contains the use of artificial intelligence”
Deep learning is no longer just a research skill — it is a core engineering competency. This course, Deep Learning Foundations for AI Engineers, is designed to take you beyond theory and help you build, train, debug, and manage deep learning systems the way real AI engineers do.
You’ll start by developing a strong conceptual foundation in neural networks, understanding how artificial neurons, forward propagation, activation functions, and loss functions work together to enable learning. Rather than memorizing formulas, you’ll build intuition through visual explanations and code-driven demonstrations.
From there, you’ll move into training deep neural networks using PyTorch, learning critical skills such as gradient descent, backpropagation, optimizer selection, and learning rate tuning. You’ll understand why models fail, how overfitting happens, and how to apply regularization techniques like L1/L2 penalties, dropout, and batch normalization to improve generalization.
This course is highly hands-on. You’ll implement:
A neural network from scratch
End-to-end training pipelines
Fully connected networks using real datasets
Image classification models with CNNs
Sequence prediction models using RNNs, LSTMs, and GRUs
You’ll also develop a strong engineering mindset by learning model saving, loading, and versioning, experiment reproducibility, debugging deep learning models, and monitoring training and validation curves — skills that are essential in production environments, not just notebooks.
By the end of the course, you won’t just “know deep learning” — you’ll think and work like a deep learning engineer, capable of building scalable, reproducible, and production-ready AI systems.
Data Science Academy
Data Science Academy is a leading provider of practical, industry-focused training in data analytics, data science, and business intelligence. With a mission to make data skills accessible to everyone, the academy designs courses that bridge the gap between theory and real-world application.
Our team of expert instructors brings years of professional experience from diverse industries, including technology, finance, healthcare, and aviation. We specialize in creating hands-on learning experiences that cover the full data lifecycle—from data collection and cleaning to analysis, visualization, and storytelling.
At Data Science Academy, we believe in learning by doing. Our courses feature step-by-step projects, interactive exercises, and real-world datasets, enabling learners to build job-ready skills in Excel, SQL, Python, Power BI, Tableau, and other leading tools.
We are passionate about empowering students to turn raw data into actionable insights that drive decision-making. Whether you are a beginner exploring data for the first time or a professional looking to upgrade your skill set, our courses are designed to help you succeed in today’s data-driven world.
Recent training programs from Data Science Academy include Python for Data Analysis, SQL for Business Intelligence, and Data Visualization with Power BI—all crafted to prepare learners for real-world analytics roles.