Online Course – Certified Professional Internship in Data and DeepLearning Implementation.AI Institute

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קורס אונליין - התמחות מקצועית מוסמכת בנתונים והטמעה של DeepLearning.AI Institute

Professional Certificate

Intermediate level

No prior knowledge required

Time to complete the course

7-day free trial

No unnecessary risks

Skills you will acquire in the course

  • Tensoflow
  • determination
  • Object recognition
  • Machine learning
  • JavaScript
  • Advanced distribution

What you will learn in the course

Courses for which the course is suitable

  • Machine learning model developer
  • TensorFlow developer
  • Data Engineer
  • Mobile app developer with machine learning
  • Artificial Intelligence Expert
  • API developer
  • Software Engineer in the field of Deep Learning
  • Data Analyst
  • Artificial Intelligence Solutions Developer
  • Data Technology Project Manager

Internship – 4-part course series

  • Come develop your TensorFlow skills and learn about a wide range of deployment scenarios.
  • Discover new ways to use data more effectively when training your deep learning models.

What will you learn in the course series?

  • How to get your deep learning models into the hands of real people on all kinds of devices.
  • Understanding how to train and run machine learning models in browsers and mobile applications.

Utilizing databases

  • Take advantage of structured databases with just a few lines of code.
  • Learn about data pipelines with TensorFlow Data Services.
  • Use APIs to control data separation.
  • Process all types of unstructured data.
  • Innovate deployed models with user data while maintaining data privacy.

Various deployment scenarios

  • Apply your knowledge to different deployment scenarios.
  • Meet TensorFlow Serving, TensorFlow Hub, TensorBoard, and more.

Artificial Intelligence in Industries

  • Industries all over the world are adopting artificial intelligence.
  • Lawrence Moroney and Andrew Ng’s expertise will help you develop and deploy machine learning models on any device or platform with speed and accuracy like never before.

A place to start

  • Master the fundamentals of TensorFlow with the DeepLearning.AI TensorFlow Developer Expert Certificate.

Powerful models

  • Want to customize and build powerful real-world models for complex scenarios?
  • Check out the TensorFlow: Advanced Techniques specialization.
Hands-on Learning Project
  • In the TensorFlow: Data and Deployment specialization, you will learn to apply your knowledge to various deployment scenarios.
  • Get to know TensorFlow Serving, TensorFlow Hub, TensorBoard, and more.
  • Implementing projects that you can add to your portfolio and present in interviews.

Details of the courses that make up the specialization

Browser-based models with TensorFlow.js

  • Course 1 • 18 hours • 4.8 (989 ratings)

Course Details

What you’ll learn
  • Train and run inference in the browser
  • Handle data in the browser
  • Build a model for classifying and identifying objects using a webcam
Skills you will acquire
  • Category: TensorFlow
  • Category: Convolutional Neural Network
  • Category: Object Recognition
  • Category: Machine Learning
  • Category: TensorFlow.js

Device-based models with TensorFlow Lite

  • Course 2 • 10 hours • 4.7 (637 ratings)

Course Details

What you’ll learn
  • Make models for battery-powered devices
  • Run models on Android and iOS platforms
  • Apply models to embedded systems, such as Raspberry Pi and microcontrollers
Skills you will acquire
  • Category: TensorFlow
  • Category: Object Recognition
  • Category: Machine Learning
  • Category: Mathematical Optimization
  • Category: TensorFlow Lite

Data Pipelines with TensorFlow Data Services

  • Course 3 • 11 hours • 4.4 (518 ratings)

Course Details

What you’ll learn
  • Perform efficient ETL tasks using the Tensorflow Data Services API
  • Build training/validation/test halves from any dataset – custom or existing in the TensorFlow Hub dataset library – using the Splits API
  • Use various TFDS API modules and functions to prepare your data for training pipelines
  • Identify bottlenecks in your input pipelines and improve your work efficiency through input parallelism
Skills you will acquire
  • Category: TensorFlow
  • Category: Extract, Transform, and Load (ETL)
  • Category: Artificial Neural Network
  • Category: TensorFlow datasets
  • Category: Data Pipes

Advanced deployment scenarios with TensorFlow

  • Course 4 • 12 hours • 4.8 (505 ratings)

Course Details

What you’ll learn
  • Use TensorFlow Serving to perform inference over the web
  • Navigate TensorFlow Hub, a repository of models that can be used for transfer learning
  • Evaluate how your models perform and share model metadata using TensorBoard
  • Explore federated learning and how to retrain deployed models while maintaining data privacy
Skills you will acquire
  • Category: Machine Learning
  • Category: TensorBoard
  • Category: Federated Learning
  • Category: TensorFlow Serving
  • Category: TensorFlow Hub

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