What you'll get
  • 7+ Hours
  • 4 Courses
  • Course Completion Certificates
  • Self-paced Courses
  • Technical Support
  • Case Studies

Synopsis

  • Advanced deep learning with TensorFlow
  • Building CNNs for images and RNNs for sequential data
  • Implementing real-world models like image captioning and face mask detection
  • Object detection, image classification, and data augmentation
  • Using TensorFlow APIs, custom layers, loss functions, and training loops
  • Optimizing model performance and applying AI to practical challenges

Content

Courses No. of Hours Certificates Details
Deep Learning with TensorFlow3h 11m✔View Curriculum
Machine Learning Project - Auto Image Captioning for Social Media2h 31m✔View Curriculum
Project on Tensorflow: Face Mask Detection Application33m✔View Curriculum
Tensorflow With Python1h 46m✔View Curriculum

Description

Google developed TensorFlow, the world's most popular deep learning library, and companies widely use it to build AI and machine learning solutions. Deep learning is a fast-growing field in computer science, with applications in computer vision, natural language processing, image generation, and signal processing. Experts in this field are in high demand and highly valued, but getting started can be overwhelming with outdated or scattered resources.

This course offers a step-by-step, project-based approach to learning deep learning with TensorFlow. You will begin with the basics and then progress to hands-on, real-world projects.

  • Deep Learning: Neural Networks with TensorFlow: Learn the basics of neural networks, activation functions, and model optimization. Implement networks for classification and regression tasks using TensorFlow.
  • Deep Learning: Automatic Image Captioning: Explore image captioning using CNNs and RNNs. Build models that generate meaningful image captions through hands-on projects.
  • Project: Face Mask Detection: Apply CNNs to detect face masks in images, gaining experience in image classification and object detection.
  • Project: Implementing Linear Regression: Build, train, and evaluate linear regression models in TensorFlow, preparing for more advanced deep learning projects.

By the end of this course, you will learn the theory and gain hands-on skills in deep learning, allowing you to work on real AI projects and grow your career.

Requirements

  • Works on Mac, Windows, and Linux

  • No prior TensorFlow knowledge required

  • Basic understanding of machine learning is helpful.

Target Audience

  • Those preparing for the TensorFlow Developer exam

  • Students, developers, and data scientists seeking hands-on ML experience

  • Anyone wanting to expand skills in AI, machine learning, and deep learning

  • Learners aiming to master ML model building with TensorFlow.