What will you in Complete Tensorflow 2 and Keras Deep Learning Bootcamp Course
Master deep learning using TensorFlow 2 and Keras from beginner to advanced level.
Build neural networks, CNNs, RNNs, and GANs for various real-world applications.
Learn techniques for natural language processing, image classification, and time series forecasting.
Use tools like TensorBoard, TFLite, and TensorFlow Serving for monitoring and deployment.
Complete hands-on projects including computer vision, NLP, and recommender systems.
Program Overview
Module 1: Introduction to TensorFlow and Keras
⏳ 30 minutes
Overview of deep learning and TensorFlow ecosystem.
Installing TensorFlow 2 and setting up development environment.
Module 2: Tensors and Basic Operations
⏳ 45 minutes
Creating and manipulating tensors.
Broadcasting, reshaping, and tensor arithmetic.
Module 3: Neural Networks with Keras
⏳ 60 minutes
Building models using Sequential and Functional APIs.
Understanding activation functions, loss functions, and optimizers.
Module 4: Image Classification with CNNs
⏳ 60 minutes
Creating convolutional neural networks from scratch.
Training models on datasets like CIFAR-10 and MNIST.
Module 5: Recurrent Neural Networks and Time Series
⏳ 60 minutes
Building RNNs, LSTMs, and GRUs for sequential data.
Time series forecasting and pattern recognition.
Module 6: Natural Language Processing (NLP) with TensorFlow
⏳ 60 minutes
Text tokenization, embeddings, and sentiment analysis.
Building NLP pipelines for classification tasks.
Module 7: Generative Adversarial Networks (GANs)
⏳ 60 minutes
Introduction to GANs and their architecture.
Creating simple image generators using GANs.
Module 8: TensorFlow Tools and Visualization
⏳ 45 minutes
Using TensorBoard for training visualization.
Model saving, checkpointing, and performance metrics.
Module 9: Model Deployment and TFLite
⏳ 45 minutes
Exporting and serving models using TensorFlow Serving.
Converting models to TFLite for mobile and embedded devices.
Module 10: Capstone Projects
⏳ 75 minutes
Real-world projects in computer vision and NLP.
Building, training, evaluating, and deploying end-to-end models.
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Job Outlook
High Demand: Deep learning skills with TensorFlow are sought after in AI, healthcare, and fintech.
Career Advancement: Ideal for ML engineers, AI developers, and data scientists.
Salary Potential: $110K–$180K+ depending on expertise and deployment ability.
Freelance Opportunities: Image classification apps, NLP solutions, recommender systems, and AI integrations.
Specification: Complete Tensorflow 2 and Keras Deep Learning Bootcamp
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