Image Captioning Skills you will learn

  • Encoder Decoder Architecture
  • Convolutional Neural Networks CNNs and Recurrent Neural Networks RNNs
  • Attention Mechanisms
  • Inference Loop

Who should learn this free Image Captioning course?

  • Machine Learning Engineers
  • Research Engineers
  • Data Scientists
  • Data Analysts

What you will learn in this Image Captioning free course?

  • Create Image Captioning Models

    • Lesson 1 : Create Image Captioning Models

      30:36
      • 1.00 Introduction
        00:25
      • 1.01 Create mage Captioning Models Overview
        11:51
      • 1.02 Create Image Captioning Models Lab Walkthrough
        18:20
      • 1.03 Knowledge check

Get a Completion Certificate

Share your certificate with prospective employers and your professional network on LinkedIn.

Why you should learn Image Captioning?

156.08 billion

Expected size of global Generative AI market by 2028.

$160K+ (USA) /INR 9 LPA

The average salary of a Machine learning engineer annually

Career Opportunities

About the Course

The course on image captioning models powered by Google Cloud provides a hands-on approach in developing image captioning models that unleashes the ability to create image captioning models with major components of image captioning models, including the encoder-decoder, attention mechanisms, convolutional neural networks (CNNs) and recurrent neural networks (RNNs) etc. In addition to this, you will learn how to train and assess your image captioning model to produce automated captions for any picture you choose that are unique to your needs. 

Read More

Get your team a digital skilling library

with unlimited access to live classes
Know More
digital skilling library

FAQs

  • What is Image Captioning in the context of Machine Learning?

    Image captioning refers to automatically generating relevant captions or textual descriptions for images using machine learning techniques.

  • What kind of models are used for Image Captioning?

    Encoder-decoder models like CNN-RNN are commonly used where a CNN encodes the image into features, and an RNN decodes it into captions.

  • Is there any prerequisite needed to start this free image captioning course?

    There are no prerequisites needed to learn this image captioning course

  • What is the duration of my access to the course?

    Upon enrollment, you will have access to the course for a period of 90 days.

  • How difficult is this course?

    The mentors and industry professionals with extensive expertise in the sector are mindful of the demands of various learners and have developed the course to be simple to learn.

  • Who can benefit from this course?

    Anyone looking to get hands-on with deep learning for computer vision and NLP can benefit, including students, engineers, researchers, and hobbyists.

  • Will I receive a certification upon completing this free course?

    Upon successful completion of the course, you will be awarded with the course completion certificate powered by Google Cloud from SkillUp.

  • What are the challenges in building Image Captioning models?

    Image captioning models face hurdles in grasping key image features, producing coherent captions, and acquiring sufficient labeled training data.

Related Courses

  • Acknowledgement
  • PMP, PMI, PMBOK, CAPM, PgMP, PfMP, ACP, PBA, RMP, SP, OPM3 and the PMI ATP seal are the registered marks of the Project Management Institute, Inc.