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IBM - Applied AI with DeepLearning 

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Applied AI with DeepLearning
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Coursera 
Overview

Upskilling is a better roadmap to success. Enroll in this course to learn critical principles of Data Science through real-life case studies & examples

Duration

24 hours

Start from

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Total fee

Free

Mode of learning

Online

Difficulty level

Intermediate

Official Website

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Credential

Certificate

Applied AI with DeepLearning
 at 
Coursera 
Highlights

  • Start instantly and learn at your own schedule.
  • Earn a certificate of learning on course completion
  • A great course for learning Data Science
  • This course is offered by IBM
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Applied AI with DeepLearning
 at 
Coursera 
Course details

Skills you will learn
What are the course deliverables?
  • Explain and apply their knowledge of Deep Neural Networks and related machine learning methods
  • Know how to use Python libraries such as PyTorch for Deep Learning applications
  • Build Deep Neural Networks using PyTorch
More about this course
  • This course, Applied Artificial Intelligence with DeepLearning, is part of the IBM Advanced Data Science Certificate which IBM is currently creating and gives you easy access to the invaluable insights into Deep Learning models used by experts in Natural Language Processing, Computer Vision, Time Series Analysis, and many other disciplines. We'll learn about the fundamentals of Linear Algebra and Neural Networks. Then we introduce the most popular DeepLearning Frameworks like Keras, TensorFlow, PyTorch, DeepLearning4J and Apache SystemML. Keras and TensorFlow are making up the greatest portion of this course. We learn about Anomaly Detection, Time Series Forecasting, Image Recognition and Natural Language Processing by building up models using Keras on real-life examples from IoT (Internet of Things), Financial Marked Data, Literature or Image Databases. Finally, we learn how to scale those artificial brains using Kubernetes, Apache Spark and GPUs
  • IMPORTANT: THIS COURSE ALONE IS NOT SUFFICIENT TO OBTAIN THE "IBM Watson IoT Certified Data Scientist certificate". You need to take three other courses where two of them are currently built. The Specialization will be ready late spring, early summer 2018
  • Using these approaches, no matter what your skill levels in topics you would like to master, you can change your thinking and change your life. If you're already an expert, this peep under the mental hood will give your ideas for turbocharging successful creation and deployment of DeepLearning models. If you're struggling, you'll see a structured treasure trove of practical techniques that walk you through what you need to do to get on track. If you've ever wanted to become better at anything, this course will help serve as your guide.
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Applied AI with DeepLearning
 at 
Coursera 
Curriculum

Tensor and Datasets

Linear Regression

Linear Regression PyTorch Way

Multiple Input Output Linear Regression

Logistic Regression for Classification

Softmax Rergresstion

Shallow Neural Networks

Deep Networks

Convolutional Neural Network

Peer Review

Applied AI with DeepLearning
 at 
Coursera 
Admission Process

    Important Dates

    May 25, 2024
    Course Commencement Date

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    Applied AI with DeepLearning
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