The Deep Learning with Tens or Flow is designed to equip learners with a solid foundation in deep learning concepts and practical implementation using Tens or Flow, one of the most powerful open-source frameworks for machine learning. This comprehensive program covers neural networks, CNNs, RNNs, autoencoders, and transfer learning, enabling participants to build and deploy advanced AI models. Through hands-on projects and real-world case studies, learners gain industry-relevant experience and develop skills required for roles in AI, data science, and machine learning engineering. Whether you’re a beginner or a professional looking to upgrade your AI expertise, this course bridges theoretical knowledge with cutting-edge practical applications in deep learning.
Key Features of Course Divine:
- Collaboration with E‑Cell IIT Tirupati
- 1:1 Online Mentorship Platform
- Credit-Based Certification
- Live Classes Led by Industry Experts
- Live, Real-World Projects
- 100% Placement Support
- Potential Interview Training
- Resume-Building Activities
Career Opportunities After Deep Learning with Tensor Flow Certified Description:
- Deep Learning Engineer
- Machine Learning Engineer
- AI Research Scientist
- Computer Vision Engineer
- Natural Language Processing (NLP) Engineer
- Data Scientist / Data Analyst
- Tens or Flow Developer
- AI/ML Consultant
- Research and Development Engineer
Essential Skills you will Develop Deep Learning with Tensor Flow Certified Description:
- Understanding of Deep Learning Concepts
- Model Development and Evaluation
- Tens or Flow Framework Proficiency
- Data Preprocessing and Augmentation
Tools Covered:
- Tens or Flow – Core framework for building and training deep learning models.
- Keas – High-level API running on top of Tensor Flow for rapid prototyping.
- Jumpy – Essential for numerical operations and array manipulations.
- Pandas – Used for data preprocessing and analysis.
- Matplotlib & Seaborne – For data visualization and plotting model performance.
- Google Cola / Jupiter Notebook – Cloud-based and local IDEs for running Python code
Syllabus:
Module 1: Introduction to Deep Learning What is Deep Learning? Difference between AI, ML, and DL Applications and real-world use cases Neural networks vs. traditional.
Module 2: Python and Math Essentials for Deep Learning Python programming basics Linear algebra, calculus, and statistics essentials Numbly and Pandas for data manipulation Matrix operations for neural networks.
Module 3: Introduction to Tens or Flow and Kera’s Installing Tens or Flow and Kera’s Tens or Flow architecture overview Tensors, graphs, and sessions First neural network with Kera’s API.
Module 4: Building Artificial Neural Networks (ANNs) Perceptron and multilayer perceptron’s Activation functions (REL, Sigmoid, Tanh) Loss functions and optimizers Backpropagation and gradient descent.
Module 5: Training Deep Neural Networks Data preprocessing and normalization Epochs, batch size, learning rate Overfitting vs. underfitting Regularization techniques: Dropout, L2.
Module 6: Convolutional Neural Networks (CNNs) CNN architecture and layers Convolution, pooling, and padding Image classification with CNNs Real-time object recognition.
Module 7: Recurrent Neural Networks (RNNs) and LSTMs Sequential data and time series RNN vs. LSTM vs. GRU Text generation and sentiment analysis Use case: stock price prediction.
Module 8: Transfer Learning and Pre-trained Models What is transfer learning? Using models like VGG, Reset, and Inception Fine-tuning and feature extraction Applications in image and NLP domains.
Module 9: Natural Language Processing with Tens or Flow Text preprocessing and tokenization Word embeddings (Word2Vec, Glove) Sequence modeling for NLP tasks Building chatbots and language models.
Module 10: Model Deployment and Capstone Project Saving and loading models Tens or Flow Lite and TensorFlow.js Deploying models on web and mobile Capstone project: End-to-end DL solution.
Industry Projects:
- Face Mask Detection Using CNN
- Sentiment Analysis on Movie Reviews
- Object Detection with Transfer Learning
Who is this program for?
- Aspiring Data Scientists
- Software Developers
- Machine Learning Enthusiasts
How To Apply:
Mobile: 9100348679
Email: coursedivine@gmail.com
