What careers can I pursue after learning deep learning basics?

This course helps you prepare for entry-level and intermediate roles such as AI Engineer, Machine Learning Engineer, Data Scientist, and AI Product positions. It also lays solid groundwork before diving into niche topics such as Generative AI.

Does this course cover Generative AI?

This course details the deep learning mechanisms that underlie generativeAI and introduces the underlying concepts such as neural networks and sequence learning. It is not specifically about GenAI tools, but rather a great foundation for anyone who wants to take on a Generative AI course.

What will I get if I purchase the Certificate?

When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Become AI-Ready: Deep Learning Fundamentals

Become AI-Ready: Deep Learning Fundamentals

Instructors: LearnKartS

3 modules

Gain insight into a topic and learn the fundamentals.

Beginner level

Recommended experience

8 hours to complete

Flexible schedule

Learn at your own pace

3 modules

Gain insight into a topic and learn the fundamentals.

Beginner level

Recommended experience

8 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

Build Neural Network Foundations to unlock AI,ML,and Generative AI career opportunities
Master Forward Pass & Backpropagationto debug, train, and optimizereal-world AI models
Decide ML vs Deep Learning Strategically to design scalable, production-ready AI systems
Understand RNNs, LSTMs & Sequence Models behind chatbots, forecasting, and GenAI apps

Details to know

Shareable certificate

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See how employees at top companies are mastering in-demand skills

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There are 3 modules in this course

Want to learn how AI systems work behind tools such as ChatGPT and develop a solid foundation for careers in AI & Generative AI?

Many professionals study AI theory but struggle to apply it to real-world systems. This course fills that gap by introducing you to how deep learning models are built, trained, and ultimately fail and get optimized in practice. Why This Course Works? 1) Real-World AI Focus – Learn where deep learning is used across GenAI, healthcare, and finance. 2) Industry Evolution Clarity – From Neural Networks → ImageNet → Generative AI shift. 3) Hands-On Understanding – Visual training using TensorFlow Playground and simulators. What You’ll Be Able To Do? -Build neural network foundations -Understand forward pass and backpropagation -Identify when to use ML vs Deep Learning -Understand RNN, LSTM, and sequence modeling This course is intended for software engineers, application developers, data analysts, professionals transitioning into AI & deep learning, as well as ML beginners who want to build job-ready AI skills. Build strong AI foundations, prepare for advanced deep learning and Generative AI roles. Enroll and start building future-ready AI skills today.

This module builds the foundation of modern AI by explaining how deep learning evolved and why it powers today’s intelligent systems. You’ll understand how AI models learn from data and how neural networks were inspired by the human brain.

What's included

16 videos5 readings7 assignments

16 videos Total 62 minutes

Why Deep Learning Is Powering Today’s AI Revolution 1 minute
What You’ll Be Able to Do After This Deep Learning Course 2 minutes
How Deep Learning Powers ChatGPT, Heathcare, and Finance Domain 4 minutes
Why Data Type Matters More Than Algorithm in AI 4 minutes
Learning Journey of Deep Learning till Gen AI 3 minutes
AI vs Machine Learning vs Deep Learning — Finally Explained Clearly 4 minutes
Types of Artifical Intelligence 3 minutes
History of Deep Learning 4 minutes
Imagenet Challenge - The Competition That Changed AI Forever 5 minutes
Transfer learning 3 minutes
Second Wave - The Moment Deep Learning Became Mainstream 5 minutes
When to Use Machine Learning vs Deep Learning 6 minutes
How AI Models Actually Learn From Data 6 minutes
How the Human Brain Inspired Neural Networks 4 minutes
How Activation Functions and Layers Power Neural Networks 4 minutes
Artificial Neural Networks 5 minutes

5 readings Total 45 minutes

Real-World Deep Learning Applications - How a Hospital Reduced Cancer Diagnosis Errors Using Deep Learning 5 minutes
From Neural Networks to Generative AI: The Industry Shift 10 minutes
Why Deep Learning Failed in the 1990s and Returned Stronger 10 minutes
From ImageNet to Generative AI: Why Deep Learning Took Off 10 minutes
How Biological Neurons Inspired Artificial Neural Networks 10 minutes

7 assignments Total 112 minutes

How AI, Machine Learning, and Deep Learning Actually Connect 25 minutes
Evolution of Deep Learning - The Breakthrough Moments That Made Deep Learning Powerful 20 minutes
How Machines Learn: From Brain Logic to Neural Networks 15 minutes
Deep Learning Foundations and Real-World Applications 8 minutes
Foundations of AI, Machine Learning, and Deep Learning 16 minutes
Evolution of Deep Learning - The Breakthrough Moments That Made Deep Learning Powerful 16 minutes
How Machines Learn: From Brain Logic to Neural Networks 12 minutes

This module takes you inside neural networks to show how deep learning models actually learn using forward pass, parameters, and backpropagation. You’ll visually explore how models improve through training, errors, and optimization.

What's included

14 videos2 readings4 assignments

14 videos Total 73 minutes

Intro to Tensorflow Playground - Train Your First Neural Network Visually 6 minutes
Tensorflow playground Intro, Epochs 7 minutes
Tensorflow Playground - Watch a Neural Network Learn in Real Time 4 minutes
Tensorflow playground learning - Simple, medium complex cases 6 minutes
When Neural Networks Fail — And How to Fix Them 4 minutes
Parameters in Deep Learning : Tensorflow Playground 1 minute
Forward pass - What Happens When Data Enters a Neural Network 5 minutes
Learning - Neural networks 7 minutes
Back Propagation - How Neural Networks Learn From Mistakes 6 minutes
Backpropagation - Gradient descent 7 minutes
Backpropagation Step-by-Step With Real Numbers 5 minutes
Forward Pass + Backprop in Action using Network Simulator 6 minutes
Forward Pass Calculations + Loss Computation in Action using Network Simulator 5 minutes
Backpropagation + Weight Updates in Action using Network Simulator 6 minutes

2 readings Total 20 minutes

Why Neural Networks Fail on Complex Patterns 10 minutes
How Data Flows Through Deep Neural Networks 10 minutes

4 assignments Total 72 minutes

Train a Neural Network Visually Using TensorFlow Playground 20 minutes
Forward Pass and Backpropagation — The Core of Deep Learning Training 20 minutes
Train a Neural Network Visually Using TensorFlow Playground 16 minutes
Forward Pass and Backpropagation — The Core of Deep Learning Training 16 minutes

This module introduces sequence intelligence and explains how AI systems handle time-based and language data using memory models. You’ll learn how RNNs and LSTMs enable AI to understand context, sequences, and long-term dependencies.

What's included

10 videos4 readings4 assignments

10 videos Total 42 minutes

RNN - Why Deep Learning Needed Memory Models 1 minute
Sequence Modeling - How AI Understands Language, Speech, and Time Data 5 minutes
Language Modeling and Need for RNN 6 minutes
Recurrent Neural Networks (RNN) Concept and Network 3 minutes
Recurrent Neural Networks (RNN) Flow and Working Mechanism 5 minutes
Challenges in RNN 5 minutes
How LSTM Solves the Memory Problem in Deep Learning 4 minutes
Understanding LSTM Gate Operations and Information Flow 5 minutes
LSTM Gradient Flow and Backpropagation Through Time 3 minutes
Course Summary 3 minutes

4 readings Total 32 minutes

Why Traditional Neural Networks Fail on Time-Based Data 10 minutes
How RNNs Remember Previous Information 10 minutes
Vanishing Gradient Problem Explained Without Math 10 minutes
Course Completion 2 minutes

4 assignments Total 45 minutes

Why Deep Learning Needs Memory: Introduction to Sequence Modeling 10 minutes
Recurrent Neural Networks Explained — And Why They Struggle 15 minutes
Why Deep Learning Needs Memory: Introduction to Sequence Modeling 8 minutes
Recurrent Neural Networks Explained — And Why They Struggle 12 minutes

Instructors

LearnKartS

133 Courses 173,172 learners

Offered by

LearnKartS

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Frequently asked questions

Deep learning fundamentals describe the core concepts that underlie neural networks, how models are trained based on data usinglayers, weights, biases, and activation functions.These ideas underpin contemporary AI systems, such as image recognition,speech processing, and smart decision-making.

Yes. This course is intended for beginners and professionals new to AI. It breaks deep learning down using intuitive explanations and easy-to-understand examples, bridging the gap between theory and practice – no AI expertise required.

Machine learning is a large field dedicated to the study of learning from data, whereas deep learning is one of its subfields that employs multi-layer neural networks. Deep learning powers AI superpowers like vision, language understanding, and pattern recognition.

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

Become AI-Ready: Deep Learning Fundamentals

Become AI-Ready: Deep Learning Fundamentals

What you'll learn

Details to know

See how employees at top companies are mastering in-demand skills

There are 3 modules in this course

Module-1: AI to Deep Learning: Foundations Behind Modern Intelligent Systems

What's included

16 videos Total 62 minutes

5 readings Total 45 minutes

7 assignments Total 112 minutes

Module-2: Inside Neural Networks: How Deep Learning Models Actually Learn

What's included

14 videos Total 73 minutes

2 readings Total 20 minutes

4 assignments Total 72 minutes

Module-3: Sequence Intelligence: RNNs, LSTMs, and AI Memory Systems

What's included

10 videos Total 42 minutes

4 readings Total 32 minutes

4 assignments Total 45 minutes

Instructors

Offered by

Why people choose Coursera for their career

Felipe M.

Jennifer J.

Larry W.

Chaitanya A.

Open new doors with Coursera Plus

Advance your career with an online degree

Join over 3,400 global companies that choose Coursera for Business

Frequently asked questions

More questions

Become AI-Ready: Deep Learning Fundamentals

Become AI-Ready: Deep Learning Fundamentals

What you'll learn

Details to know

See how employees at top companies are mastering in-demand skills

There are 3 modules in this course

Module-1: AI to Deep Learning: Foundations Behind Modern Intelligent Systems

What's included

Module-2: Inside Neural Networks: How Deep Learning Models Actually Learn

What's included

Module-3: Sequence Intelligence: RNNs, LSTMs, and AI Memory Systems

What's included

Instructors

Offered by

Why people choose Coursera for their career

Felipe M.

Jennifer J.

Larry W.

Chaitanya A.

Open new doors with Coursera Plus

Advance your career with an online degree

Join over 3,400 global companies that choose Coursera for Business

Frequently asked questions

What are deep learning fundamentals?

Is this Coursera deep learning course suitable for beginners?

How is deep learning different from machine learning?

More questions