Introduction To AI/ML for Engineers & Non-Engineers Training

Live Online & Classroom Enterprise Training

This beginner-friendly course introduces the fundamentals of AI/ML. Ideal for both engineers and non-engineers, it covers key concepts, real-world applications, and hands-on exercises. Build a strong foundation to confidently explore more advanced AI/ML topics in future learning modules.

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What is Introduction To AI/ML for Engineers & Non-Engineers Training about?

This introductory course offers a comprehensive overview of Artificial Intelligence (AI) and Machine Learning (ML) designed for both engineers and non-engineers. Participants will learn the fundamental principles and terminology of AI/ML, making complex concepts accessible to those with varying levels of technical expertise. The course delves into practical applications, demonstrating how AI/ML technologies are implemented across different industries through real-world examples and case studies.

Interactive sessions and hands-on exercises are integral to the curriculum, providing practical experience in applying theoretical knowledge. By the end of the course, participants will have a solid foundation in AI/ML, equipping them with the confidence and knowledge to pursue more advanced studies or integrate AI/ML into their professional skillset.

What are the objectives of Introduction To AI/ML for Engineers & Non-Engineers Training ?

Explore Real-World Applications: Learn how AI/ML technologies are applied across various industries through practical examples and case studies.
Understand Fundamental Concepts: Gain a solid understanding of the basic principles and terminology of Artificial Intelligence (AI) and Machine Learning (ML).
Develop Practical Skills: Engage in hands-on exercises and interactive sessions to apply theoretical knowledge to real-world scenarios.
Build a Strong Foundation: Establish a foundational knowledge base to confidently progress into more advanced AI/ML topics.
Cater to Diverse Backgrounds: Ensure that both engineers and non-engineers can grasp and utilize AI/ML concepts effectively.
Enhance Career Prospects: Equip participants with the skills and insights needed to integrate AI/ML into their professional skillset and career paths.

Who is Introduction To AI/ML for Engineers & Non-Engineers Training for?

Engineers: Professionals in technical fields looking to integrate AI/ML into their skillset and enhance their career prospects.
Non-Engineers: Individuals from non-technical backgrounds who are interested in understanding AI/ML concepts and their applications in various industries.
Students: Learners seeking to build a strong foundational knowledge of AI/ML before pursuing more advanced studies.
Career Changers: Professionals from any industry who wish to pivot their careers towards AI/ML and related fields.
Business Leaders: Managers and executives aiming to comprehend the impact of AI/ML on their industries to make informed strategic decisions.
Tech Enthusiasts: Anyone with a curiosity about AI/ML who wants to gain a deeper understanding of these technologies and their potential.

What are the prerequisites for Introduction To AI/ML for Engineers & Non-Engineers Training?

Basic Computer Literacy
Curiosity and Interest
No Prior Technical Knowledge Required
Open Mindset

Available Training Modes

Live Online Training

8 Hours

Classroom Training

1 Days

Course Outline Expand All

Expand All

What is ML, DS, AI, NLP, DL? Demystifying these terms

Use cases of ML

Use cases of processes that are NOT ML

Supervised ML, Unsupervised ML

Examples of Supervised ML, Unsupervised ML

Videos of ML

Regression and Classification

What is Data Science?

Most important step in ML, DS - DATA

Define Problem and success measures

Do a Pilot to solve above (This is process point)

Understand Benchmarks and SOTA

EDA - Understand Data, Clean Data, Choose fields

CRISP-DM Process for project execution

Getting Data based on different scenarios (Data Rich, public, outsource and create own data by designing experiments and data augmentation)

Regression and Classification Algorithms

Types of data - quantitative and Qualitative and challenges with those data

KNN algorithm

What is KNN

with Challenges KNN

When to avoid using KNN

When it can be used

Embedded Algorithm

Who is the instructor for this training?

The trainer for this Introduction To AI/ML for Engineers & Non-Engineers Training has extensive experience in this domain, including years of experience training & mentoring professionals.

Introduction To AI/ML for Engineers & Non-Engineers Training - Certification & Exam

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