This intermediate learning path is for people who want to build their understanding of tensorflow fundamentals and model building through video explanations and independent practice.
About this course
Learn tensorflow fundamentals and model building with free video lessons from Simplilearn. TensorFlow concepts, dataflow graphs, program structure and introductory implementation examples. Study at your own pace in the WikiFree classroom.
Course at a glance
| Provider | Simplilearn |
|---|---|
| Platform | YouTube · Simplilearn |
| Access | Free Video |
| Level | Intermediate · WikiFree audience assessment |
| Language | English |
| Selected lessons | 13 |
| Video duration | 4h 16m · additional practice time is recommended |
| Format | Self-paced video learning |
| Details checked | 11 October 2026 |
What you’ll learn
- Explore tensorFlow concepts, dataflow graphs, program structure and introductory implementation examples.
- Follow the selected explanations of Dataflow Graphs, Model Basics and Use Cases.
- Connect concepts to lessons such as Lesson – 04 — Program Elements In TensorFlow.
- Practise independently: Describe a small TensorFlow model's inputs, operations and outputs, then compare its predictions with sample labels.
Skills you’ll gain
- Dataflow Graphs
- Model Basics
- Use Cases
Course Overview
TensorFlow concepts, dataflow graphs, program structure and introductory implementation examples. The classroom brings together 13 selected learning videos from Simplilearn’s public YouTube course playlist. You can follow the sequence or use the lesson search to revisit a particular subject.
The selected curriculum includes the following lesson examples:
- Lesson – 01 — Introduction to TensorFlow
- Lesson – 04 — Program Elements In TensorFlow
- Lesson – 07 — Tensorflow 1.0 vs 2.0
- Lesson – 10 — Recurrent Neural Networks
- Lesson – 12 — Libraries Required
Each course retains its relevant lessons, including videos also used in another course. Numbered series follow their original lesson or part order. Only reviewed advertisements, unrelated items and identical repeated playlist entries are excluded. Source recordings may have been made at different times.
Who is this for?
This intermediate learning path is for people who want to build their understanding of tensorflow fundamentals and model building through video explanations and independent practice.
Python and basic machine-learning knowledge are recommended. Older demonstrations may need adaptation to your installed TensorFlow version.
Put the lessons into practice
Describe a small TensorFlow model's inputs, operations and outputs, then compare its predictions with sample labels.
This is an optional WikiFree practice suggestion, not a graded assignment supplied by Simplilearn. Pause the videos when a concept is unfamiliar, keep notes and repeat a small example before moving on.
Certificate / Assessment
The public YouTube lessons are free to watch. This listing does not include a Simplilearn certificate, an accredited qualification, a provider-marked examination or instructor feedback. Separate Simplilearn programs can have their own enrollment and certificate requirements.
Mark complete is a personal progress tracker. It does not assess your answers or verify that you have mastered the lesson.
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Intermediate
Compare course focus, level and study time
| Course | Level | Focus | Study time |
|---|---|---|---|
| This course — Free Simplilearn Course: TensorFlow Fundamentals and Model Building | Intermediate | Dataflow Graphs · Model Basics · Use Cases | 4h 16m of video; practice time is additional |
| Free Simplilearn Course: Deep Learning and Neural Networks | Intermediate | Neural Networks · CNNs · RNNs | 78h 16m of video; practice time is additional |
| Google Encoder-Decoder Architecture: Free Deep Learning Course | Intermediate | Sequence-to-sequence concepts · Encoder-decoder architecture · Text generation workflow literacy | 30 minutes; individual study pace varies |
| Free MIT Course: Applied Deep Learning and Generative AI | Intermediate | 1: Introduction to Neural Networks and Deep Learning; Training Deep NNs · 3: Deep Learning for Computer Vision – Building Convolutional Neural Networks from Scratch · 6: Deep Learning for Natural Language – Embeddings | 13h 45m of video; practice time is additional |
Frequently asked questions
Is this Simplilearn course free?
Yes. The selected public YouTube videos can be watched for free. Any software, cloud service, hardware or separate certification mentioned in the videos has its own access conditions.
What should I know before starting?
Python and basic machine-learning knowledge are recommended. Older demonstrations may need adaptation to your installed TensorFlow version.
How long does the course take?
The selected videos total 4h 16m. Your study time can be longer because of notes, repeated examples and independent practice.
Does watching the videos give me a certificate?
No certificate is included with this WikiFree YouTube listing. Watching videos or marking them complete does not earn a Simplilearn qualification.
Can I study on my phone?
Yes. Use the responsive video player and lesson list on a phone, tablet or computer. Programming, software and hardware exercises may be easier on an appropriate computer or device.
Are all demonstrations current?
The playlist includes recordings made at different times. Software interfaces, services and exam requirements can change; check the current official documentation when reproducing a demonstration.
Source: Simplilearn’s official YouTube course playlist.
Provider: Simplilearn. Videos play from the Simplilearn channel on YouTube.
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