Machine Learning & Artificial Intelligence for Mechanical, Civil & EE Engineers using Python

Machine Learning & Artificial Intelligence for Mechanical, Civil & EE Engineers

  • 0% EMI Option Available
  • Pre-requisites : For Mechanical, Automotive & Aerospace, Electrical & Electronics & Civil Engineers
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A Quick Overview

Many students perceive Machine Learning and Artificial Intelligence to be magic keywords. At the end of the day, AI and ML are nothing but statistical tools that you can use to understand your data. Machine Learning and Artificial Intelligence have been around for over 50+ years, the first perception did not do a great job. The first idea of back-propagation emerged 30 years back. However, now we are in an amazing sweet spot, where ML and AI algorithms are matched by the equally-amazing modern-day computer.
 
This course in ML and AI is specifically designed for Mechanical, Civil and Electrical & Electronics Engineers to get acquainted with essential mathematical concepts, brush up on their statistics and the fundamentals of ML and AI. 
 

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COURSE SYLLABUS

1Basics of Probability and Statistics

In this module, we will introduce the ideas of Statistics, machine learning and artificial intelligence. 

Basics of Probability

Basics of Statistics

What is ML & AI


2Basics of ML & AI

In this section, we start with supervised learning

Introduction to normal distribution & standard normal distribution

Introduction to business moments

Artificial Intelligence


3Supervised Learning - Prediction

In this section, we start with supervised learning

Introduction to supervised learning

What is linear regression

One hot encoding

Cost function and gradient descent

    

4Supervised Learning - Classification

In this section, we start with classification algorithm

Introduction to classification problems

What is logistic regression

Cost function and gradient descent


5Supervised Learning - Classification

In this module, we will introduce some more classification algorithms

Decision tree

Entropy

Information gain


6Random forest & Model Evaluation

In this section, we will assess the algorithms

Random Forest

Bootstrapping and majority rule

Evaluation of classifiers


7Supervised Learning - Classification

In this module, we will introduce SVM

Support Vector Machines

Mathematical intuition behind SVM 

How SVM is different from other classifiers


8Supervised Learning - Classification

In this section, we will introduce knn

K-Nearest Neighbour

Lazy Algorithm

Single layer Neural Network


9Unsupervised Learning - Kmeans

In this section, we will introduce clustering

What is clustering

Why clustering is important

Kmeans and elbow curve


10Unsupervised Learning - Hierarchical

In this section, we will introduce another type of clustering

Hierarchical Clustering

Dendrogram

Evaluation of clustering algorithms


11Unsupervised Learning - PCA

In this module, we will introduce some feature selection techniques

Feature Selection

Principal Component Analysis

Mathematical intuition behind PCA


12Supervised Learning - Classification

In this section, we will introduce neural network

Artificial Neural Network

Deep learning

Different activation functions

Understanding back propagation



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Our courses have been designed by industry experts to help students achieve their dream careers

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WHO IS THIS COURSE FOR ?


  • Students of Mechanical, Electrical & Electronics, Civil and Computer Science Engineering
  • Freshers and Professionals looking to understand the basics of ML & AI

Programming Language


Flexible Course Fees

Choose the plan that’s right for you

Basic

2 Months Access

$94.08

Per month for 3 months

  • Access Duration : 2 months
  • Mode of Delivery : Online
  • Project Portfolio : Available
  • Certification : Available
  • Email Support : Available
  • Forum Support : Available
Premium

Lifetime Access

$201.6

Per month for 3 months

  • Access Duration : Lifetime
  • Mode of Delivery : Online
  • Project Portfolio : Available
  • Certification : Available
  • Individual Video Support : 12/month
  • Group Video Support : 12/month
  • Email Support : Available
  • Forum Support : Available
  • Telephone Support : Available
  • Add-ons Industry Projects : 2
  • Dedicated Support Engineer : Available

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Certification

  • Top 5% of the class will get a merit certificate
  • Course completion certificates will be provided to all students
  • Build a professional portfolio
  • Automatically link your technical projects
  • E-verified profile that can be shared on LinkedIn

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Frequently Asked Questions

1Who are the instructors and what is the learning process?

Our instructors are industry experts working in Fortune 500 companies. We partner with them to deliver the lectures online. You will be given access to recorded content and assignments each week.

2Are there any prerequisites for this course?

You should be pursuing or have graduated with a B.E/B.Tech in Mechanical or Computer Science Engineering.

3What kind of support I can expect? What if I have doubts?

Our support system is amazing!. You can read our reviews on Google to see this. We focus on one-on-one support which no one else does. We will communicate with you through videoconferencing, WhatsApp messages/calls, individual online sessions and also in person. Doubts and queries are addressed by a dedicated support engineer who is assigned to you to walk you through your problem areas and clarify any queries that you may have.


4How is this different from what I learnt in college?

Our courses are crafted after consultation with industry experts. This gives you the opportunity to apply what you have learned only as theory and work on projects that will give you a leg up in your career aspirations - be it an MS admit, a new job or growth within your organization. This course will help you bridge the gap between academia and industry and get you market-ready.


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