An In-depth Analysis of Coursera's Deep Learning Specialization

Vishaal Karthik B

07 June 2023

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Course Overview

In Introduction to Artificial Intelligence (AI) by Coursera, you will learn what Artificial Intelligence (AI) is, explore use cases and applications of AI, and understand AI concepts and terms like machine learning, deep learning and neural networks. In deep learning specialization coursera course, you will be exposed to various issues and concerns surrounding AI, such as ethics and bias, jobs, and get advice from experts about starting a career in AI.

You will also demonstrate AI in action with a mini-project. This coursera deep learning course does not require any programming or computer science expertise and is designed to introduce the basics of AI to anyone, regardless of whether they have a technical background.

Rav Ahuja, the instructor for this deep learning course, is a Global Program Director at International Business Machines (IBM). Rav leads growth strategy, curriculum creation, and partner programs for the IBM Skills Network. This instructor was well experienced enough to explain each and every point in an easy manner. With his great teaching skills, he plays a major role in making the course understandable.

"The course provided a crucial understanding of AI in a structured way so that I am able to apply my knowledge to various fields pragmatically."

- Vishaal Karthik B

Course Structure

It is a self-paced, well-curated beginner level deep learning online course spread over a duration of 9 hours. This program taught online by experienced faculty members usually requires learners to put in 2.5 hours per sitting.

In the initial 2 weeks, the basics of cloud and various cloud providers are discussed. The following weeks focus on the detailed explanation on the major Amazon Web Services (AWS) available for personal and organizational use. In the last week, the financial benefits of using AWS compared to other cloud providers was discussed.

Technically, the deep learning coursera course is spread over 4 distinct modules:

Module 1: What is AI? Applications and Examples of AI.
Module 2: AI Concepts, Terminology, and Application Areas.
Module 3: AI: Issues, Concerns and Ethical Considerations.
Module 4: The Future with AI, and AI in Action.

Insider Tips

In order to get the best out of this deep learning specialization coursera course, below I have included some important tips that I think you might find useful:

Technical Exhibitionism from the Course

In this deep learning certification course, you will learn what AI is, understand its applications and use cases and how it is transforming our lives. You will explore basic AI concepts, including machine learning, deep learning, and neural networks, as well as use cases and applications of AI.

Assessment and Grading Criteria

The assessment method requires completing assignments and undertaking projects under various modules throughout the degree. These can be research-based or concept specific. You will take a glimpse of the future with AI, get advice for starting an AI-related career, and wrap up the course by demonstrating AI with a mini-project.

The evaluations are designed to ensure continuous student engagement with the program and to encourage learning. There are instructor-moderated discussions kept in stipulated intervals to validate the learning experience of the learners.

Final Take

I'm currently pursuing my Bachelors in Mechatronics from the Thiagarajar College of Engineering, Madurai in India. Being a Mechatronics student, it is crucial for me to understand AI in a structured way in order to pragmatically apply my knowledge in fields like self-driving cars.