- What is AI and Deep Learning
- Applications of Deep Learning
- Brief History of AI
- Recap: SL, UL and RL
- Deep Learning: Successes Last Decade
- Demo and Discussion: Self-Driving Car Object Detection
- Key Takeaways
- Knowledge Check
- Challenges of Deep Learning
- Demo and Discussion: Sentiment Analysis Using LSTM
- Full Cycle of a Deep Learning Project
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- Deep Learning Course with Keras and Tensorflow Certification Training
Deep Learning Course (with Keras and Tensorflow) Certification Training
The Deep Learning course (with Keras and Tensorflow) certification training course provides extensive guidance of Deep Learning and Machine Learning.
Online
14 Days
₹ 22,470
Quick facts
particular | details | ||
---|---|---|---|
Medium of instructions
English
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Mode of learning
Self study, Virtual Classroom
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Mode of Delivery
Video and Text Based
|
Frequency of Classes
Weekdays, Weekends
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Course overview
The Deep Learning course (with Keras and Tensorflow) certification training course, will educate participants on deep learning concepts and models using Keras and TensorFlow frameworks, to carry out deep learning algorithms. The Deep Learning course (with Keras and Tensorflow) certification training online provides 34 hours of blended learning, industry projects, and dedicated project mentoring sessions from industry experts that will help you prepare for a career as a Deep Learning engineer.
The Deep Learning course (with Keras and Tensorflow) certification training offers you a competitive edge in solving applications without human intervention. The training provides you with ways of expanding the limits of what a computer system can accurately inspect. The Deep Learning course (with Keras and Tensorflow) certification training online will help you differentiate between Deep Learning, Machine Learning, and Artificial Intelligence.
Deep Learning course (with Keras and Tensorflow) certification training by Simplilearn benefits IT developers and testers, data analysts, junior data scientists, analytics professionals, software engineers, statisticians, students, and professionals indulging in data across every field. The Deep Learning course (with Keras and Tensorflow) certification training online will help the candidates in creating deep learning models to interpret the results in building a deep learning project.
The highlights
- 34 hours of blended learning
- Two Real-life industry-based projects
- Dedicated project mentoring sessions
- Flexible class timings
- 100% money-back guarantee
Program offerings
- Blended learning
- Corporate training
- Industry based projects
- Dedicated monitoring sessions
- Flexible timings
Course and certificate fees
Fees information
The Deep Learning course (with Keras and Tensorflow) certification training fee is around Rs. 23,592 for all the participants.
Deep Learning course with (Keras and Tensorflow) certification training fee Details
Training Options | Fee |
Blended Learning | Rs. 22,470.00 + Rs. 4,044.60 (CGST + SGST) = Rs. 26,514.60 |
Corporate Training | Not available |
certificate availability
certificate providing authority
Eligibility criteria
Certification Qualifying Details
The Deep Learning course (with Keras and Tensorflow) certification training shall be awarded once the course is completed.
What you will learn
Once you complete the Deep Learning course (with Keras and Tensorflow) certification training syllabus, you will be adept in skills such as –
- Use an open-sourced framework like TensorFlow and a high-level API like Keras and benefit from the vast library of deep neural networks
- With improved processing power you can use these two frameworks for deep learning projects in the most popular languages like C, C++, Python, Java, Android, Linux, Windows, IoS, and many more
- Learn to use PyTorch and its elements which will give you simpler and faster Python codes to generate dynamic computational graphs.
- The use of PyTorch will ensure better optimization of data.
- Analyse visual elements with the help of Convolutional Neural Networks (CNN), while working on image classification
- Speed up your image classifying process and increase its efficiency
- Use ANNs in pattern recognition software, while also utilising them in making machine learning models
- Learn to use Autoencoders to develop models of image processing, anomaly detection, machine translation, and other deep learning models
- Utilise Deep Neural Networks in a variety of models based on deep learning for increased computation power, like speech recognition, audio recognition, image analysis, and machine vision
- Analyse large pools of raw and unsegmented data with the use of rich recurrent neural networks
- Understand the role of optimizers to establish and reform the weight parameters in diminishing the loss function
Who it is for
The Deep Learning course with (Keras and Tensorflow) certification training course is highly suitable for professionals interested in getting acquainted with deep learning concepts across industries like IT, finance, and more. Some common profiles include –
Admission details
Filling the form
For the application process, follow the steps below:
- Visit the official website of the providers.
- Click on Enroll now button and it will redirect to a new page.
- If applicants have a coupon then they have to apply this or just click on the Proceed button.
- Fill in the necessary learner's details like name, email, and contact number and proceed.
- Pay the necessary fee and save the receipt of the transaction.
The syllabus
Introduction
Artificial Neural Network
- Neural Network Training a Perceptron
- Demo Code #1: Perceptron (Linear Classification)
- Backpropagation
- Biological Neuron Vs Perceptron Shallow
- Role of Activation Functions and Backpropagation
- Demo Code #2: Activation Function
- Demo Code #3: Backprop Illustration
- Optimization
- Regularization
- Dropout layer
- Demo Code #4: Dropout Illustration,
- Lesson-end Exercise (Classification Kaggle Dataset) Key Takeaways
- Knowledge Check
- Lesson-end Project
Deep Neural Network & Tools
- How to Choose Your Loss Function?
- Demo Code #5: Build a Deep Learning Model Using Keras
- Tensorflow and Its Ecosystem
- Deep Neural Network: Why and Applications
- Designing a Deep Neural Network
- Tools for Deep Learning Models
- Keras and its Elements
- Demo Code #6: Build a Deep Learning Model Using Tensorflow
- TFlearn
- Pytorch and its Elements
- Demo Code #7: Build a Deep Learning Model Using Pytorch
- Demo Code #8: Lesson-end Exercise
- Key Takeaways
- Knowledge Check
- Lesson-end Project
Deep Neural Net optimization, tuning, interpretability
- Demo code #9: MNIST Dataset
- Batch Normalization
- Demo Code #10
- Optimization Algorithms
- Exploding and Vanishing Gradients
- Hyperparameter Tuning
- SGD, Momentum, NAG, Adagrad, Adadelta , RMSprop, Adam
- Demo Code #11
- Interpretability
- Demo Code#12: MNIST– Lesson-end Project with Interpretability Lessons
- Width vs Depth
- Key Takeaways
- Knowledge Check
- Lesson-end Project
Convolutional Neural Net
- Key Takeaways
- Knowledge Check
- Demo Code #13: Keras
- Success and History
- CNN Network Design and Architecture
- Demo Code #14: Two Image Type Classification (Kaggle), Using Keras
- Deep Convolutional Models
- Lesson-end Project
Recurrent Neural Networks
- Sequence Data
- Sense of Time
- RNN Introduction
- Demo Code #15: Share Price Prediction with RNN
- LSTM (Retail Sales Dataset Kaggle)
- Demo Code #16: Word Embedding and LSTM
- Demo Code #17: Sentiment Analysis (Movie Review) GRUs
- LSTM vs GRUs
- Demo Code #18: Movie Review (Kaggle), Lesson-end Project)
- Key Takeaways
- Knowledge Check
- Lesson-end Project
Autoencoders
- Introduction to Autoencoders
- Demo Code #19: Autoencoder Model for MNIST Data
- Applications of Autoencoders
- Autoencoder for Anomaly Detection
- Key Takeaways
- Knowledge Check
- Lesson-end Project
Evaluation process
The Deep Learning course with (Keras and Tensorflow) certification training certification exam contains five categories and students will have to complete these five models, one from each category.
Deep Learning course (with Keras and Tensorflow) certification training by Simplilearn exam duration will be five hours. The TensorFlow Developer certification exam costs INR 7,432 or USD $100, which includes three exam attempts.
How it helps
Upon completion of the Deep Learning course with (Keras and Tensorflow) certification training, participants will acquire an industry-recognized course completion certificate with lifelong validity after the completion of the course. You can find lucrative roles as a data scientist or a machine learning engineer in diverse industries such as healthcare, information technology, fin-tech, and e-commerce. As a certified Deep Learning professional, you can earn up to 13 Lakhs per annum.
In fact, several top recruiters such as Accenture, Oracle, Walmart, NVIDIA, Microsoft, and many more are always on the lookout for certified Data Learning professionals so you can get opportunities without fail.
FAQs
You can attempt the Deep Learning course with (Keras and Tensorflow) certification training exam up to three times.
There are no prerequisites for the Deep Learning course (with Keras and Tensorflow) certification training by Simplilearn; however knowledge of programming, statistics, and machine learning will help.
The certification training course familiarises you with the language and the elementary concepts of deep learning and you learn how to create deep learning models.
Yes, you will receive the completion certificate after you finish the online self-learning training, practical exercises, and the two on-hand industry-based projects.
You will have 5 hours to complete and submit the exam.
You have three attempts to pass the TensorFlow Developer exam.