Introduction to TensorFlow for AI, ML, and Deep Learning Certified Course

Course De4scription:

The Introduction to TensorFlow for AI, ML, and Deep Learning course is designed to equip learners with a strong foundation in using TensorFlow, one of the most popular open-source frameworks for building machine learning and deep learning models. This course covers the essential concepts of artificial intelligence, machine learning, and deep learning, while providing hands-on experience in developing models using TensorFlow. Learners will gain practical skills to build, train, and deploy AI models effectively.

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 Introduction to TensorFlow for AI, ML, and Deep Learning certified course:

• Machine Learning Engineer
• Deep Learning Specialist
• AI Developer
• Data Scientist
• AI Researcher

Essential Skills you will Develop Introduction to TensorFlow for AI, ML, and Deep Learning certified course:

• Understanding core AI, ML, and DL concepts.
• Hands-on experience with TensorFlow for real-world projects.
• Building and training machine learning models from scratch.
• Implementing neural networks for image, text, and structured data.
• Model evaluation, tuning, and deployment strategies.
• Working knowledge of Python libraries for AI and ML, such as Numbly, Pandas, and Matplotlib.

Tools Covered:

• TensorFlow 2.x
• Keras API
• Python, NumPy, Pandas, Matplotlib
• Jupyter Notebooks / Google Colab

Syllabus:

Module 1:

Introduction to AI, ML, and Deep Learning Overview of Artificial Intelligence, Machine Learning, and Deep Learning Types of machine learning: Supervised, Unsupervised, and Reinforcement Learning Applications of AI and ML in real-world scenarios Introduction to AI frameworks and tools.

Module 2:

Getting Started with TensorFlow Installing TensorFlow and setting up the environment Introduction to TensorFlow 2.x Understanding tensors and basic TensorFlow operations Overview of Keras API.

Module 3:

Tensors and Tensor Operations Creating and manipulating tensors Tensor indexing, slicing, and reshaping Mathematical operations with tensors Broadcasting and advanced tensor operations.

Module 4:

Machine Learning with TensorFlow Building simple regression and classification models Loss functions, optimizers, and metrics Training and evaluating ML models Using datasets with TensorFlow.

Module 5

Introduction to neural networks Activation functions and their importance Forward and backward propagation Understanding model loss, accuracy, and evaluation metrics.

Module 6:

Convolutional Neural Networks (CNNs) Understanding CNN architecture and layers Building image classification models Implementing pooling and convolution layers Practical projects on image recognition.

Module 7:

Recurrent Neural Networks (RNNs) and LSTM Understanding sequence modeling Building RNN and LSTM models Applications in time-series prediction and NLP Hands-on project with sequential data.

Module 8:

Model Optimization and Regularization Techniques to improve model performance Dropout, batch normalization, and early stopping Hyperparameter tuning Preventing overfitting and underfitting.

Module 9:

TensorFlow Data Pipelines Handling large datasets efficiently Preprocessing and augmenting data Using TensorFlow Dataset API Data loading, shuffling, and batching.

Module 10:

Model Deployment and Real-World Projects Saving and loading trained models Exporting models for web and mobile applications Deployment using TensorFlow Serving or TFLite.

Industry Projects:

• Handwritten Digit Recognition (MNIST Dataset)
• Image Classification with Convolutional Neural Networks (CNNs)
• sentiment Analysis with Recurrent Neural Networks (RNNs) / LSTM

 Who is this program for?

• Beginners in AI and ML
• Software Developers and Engineers
• Data Enthusiasts and Analysts

How To Apply:

Mobile: 9100348679

Email: coursedivine@gmail.com