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Machine Learning Fundamentals In Depth

A comprehensive course on the fundamentals of Machine Learning and Artificial Intelligence using Python required to excel in the industry.

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Syllabus

This course is full of best-in-class content by leading faculty and industry experts in the form of videos and projects

Course Overview

More and more industries are relying on machine learning to develop systems that function on their own through repetitive learning. As machine learning is widespread across a variety of domains and industries, it has become a standard prerequisite for engineers striving to work in the industry. This course will offer aspiring engineers a solid understanding of the fundamental machine learning algorithms.

You will learn about...

  • Basic probability and statistics essential for understanding ML and AI
  • Supervised learning (Prediction, classification)
  • Random Forest and Model Evaluation
  • Unsupervised Learning (K Means, Hierarchical, PCA)

In addition to the theory taught in this course, you will get hands-on exposure to the use of Python for machine learning applications. This course culminates with industry level projects focused on real-time application of machine learning concepts. 

Who can enrol in this course?

Engineering graduates and working professionals with a background in similar fields can take this course.

Course Syllabus

On a daily basis we talk to companies in the likes of Tata Elxsi and Mahindra to fine tune our curriculum.

Week 1 - Basics of Probability and Statistics

This week, you will learn about

  • Basics of Probability
  • Basics of Statistics
  • What ML & AI is

Week 2 - Basics of Machine Learning (ML) & Artificial intelligence (AI)

This week, you will learn about 

  • Normal Distribution & Standard Normal Distribution: Introduction
  • Business Moments: Introduction
  • Artificial Intelligence

Week 3 - Supervised Learning - Prediction

This week, you will learn about 

  • Supervised learning: Introduction
  • What linear regression is
  • One hot encoding
  • Cost function and gradient descent

Week 4 - Supervised Learning - Classification

This week, you will learn about 

  • Classification problems: Introduction
  • What logistic regression is
  • Cost function and gradient descent

Week 5 - Supervised Learning - Classification

This week, you will learn about 

  • Decision tree
  • Entropy
  • Information gain

Week 6 - Random Forest & Model Evaluation

This week, you will learn about 

  • Random forest
  • Bootstrapping and majority rule
  • Evaluation of classifiers

Week 7- Supervised Learning - Classification

This week, you will learn about 

  • Support Vector Machines (SVM)
  • Mathematical intuition behind SVM
  • How SVM is different from other classifiers

Week 8 - Supervised Learning - Classification

This week, you will learn about 

  • K-Nearest Neighbor
  • Lazy Algorithm
  • Single-layer Neural Network

Week 9 - Unsupervised Learning - K-Means

This week, you will learn about

  • What clustering is
  • Why clustering is important
  • K Means and elbow curve

Week 10 - Unsupervised Learning - Hierarchical

This week, you will learn about

  • Hierarchical Clustering
  • Dendrogram
  • Evaluation of clustering algorithms

Week 11 - Unsupervised Learning - PCA

This week, you will learn about 

  • Feature Selection
  • Principal Component Analysis (PCA)
  • Mathematical intuition behind PCA

Week 12 - Supervised Learning - Classification

This week, you will learn about

  • Artificial Neural Networks
  • Deep learning
  • Different activation functions
  • Understanding back propagation

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

Industry Projects

Our projects are designed by experts in the industry to reflect industry standards. By working through our projects, Learners will gain a practical understanding of what they will take on at a larger-scale in the industry. In total, there are 2 Projects that are available in this program.

Descriptive Analysis and Regression Analysis

In this project, you will perform descriptive analysis on given data regarding cars. Using the data, you will have to classify cars based on various parameters and analyze the pricing trends. You will then have to use Python to read the data and identify parameters on which data cleaning has to be performed. In addition to this, you will create a correlation matrix to identify predominant characteristics and then perform regression analysis on them. 

K-Means Clustering

In this project, you will have to clean a data set regarding cars and implement the clustering algorithm using K-Means. You will then have to explain the results and find the optimum values using the Elbow curve.

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

Ratings & Reviews by Learners

Skill-Lync has received honest feedback from our learners around the globe.

Google Rating
4.8

Excel in your career with our Machine Learning Fundamentals In-Depth course

The main objective of this Machine Learning Fundamentals In Depth course is to teach you from basics to advanced concepts. Expertise in Machine Learning and Artificial Intelligence will help you secure lucrative career opportunities. Knowledge of Machine Learning and Artificial Intelligence will help you predict customer behavior patterns. This could make you a key decision-maker in organizations.

This AI & ML course will cover both supervised and unsupervised learning in Machine Learning. You will learn about the basics of statistics and probability, which form the base of the subject. You will also get in-depth knowledge of what is AI & ML through this course.

Who Should Take This Course?

Industrial experts have designed this course for students and graduates from Computer Science and Information Technology backgrounds. The machine learning course is also for mechanical engineers interested in this domain. This AI and ML course is highly suited for beginners who want to start from the basics.

Whoever is interested in building Machine Learning and Artificial Intelligence systems can take this course. As one of the best AI ML courses, this course is curated as per industry standards.

If you are looking for AI ML courses online to upskill yourself with the ongoing trends in technologies, this course will suit you well.

What Will You Learn in This Course?

Through this Machine Learning Fundamentals In Depth, you will learn industry-relevant concepts in this AI & ML course. In the first week, you will be introduced to the basic concepts of statistics and probability needed for a good understanding of AI and ML concepts. As you progress through the, you will cover the basics of ML and Al and business moments. Along with that, you will also learn what is AI & ML.

You will start learning supervised and unsupervised learning. You will explore the Random forest, Bootstrapping, and majority rule concepts. Key concepts include logistic regression, which is used for prediction analysis and cost function and gradient descent will be covered. Some mathematics concepts applied in Support Vector Machines will be covered in the curriculum. Concepts of clustering and clustering algorithms, and you will understand what is Deep Learning through this AI ML course. In this course, you will work on descriptive analysis and regression analysis, and K-means clustering, which are industry projects.

Towards the end of the artificial intelligence and machine learning course, you will be capable of performing descriptive analysis and regression analysis. Our experts will teach all the essential concepts to find the relationship between different variables and train machine learning algorithms.

As one of the best machine learning courses, it will impart key technical skills to make you competent in the job market. You will be working on an industry-level project in which you need to clean the data set using K-means clustering during your coursework.

Skills You Will Gain

  • By working on real-time projects, you will become industry-ready.
  • A sound understanding of concepts involved in AI and ML.
  • You will gain skills in Deep Learning which is a key technology for many applications.
  • Also, a knowledge of mathematics will enhance your analytical skills.

Key Highlights of the Program

  • The duration of the machine learning and artificial intelligence course is 12 weeks.
  • Besides the course completion certificate for all participants, the top 5% of learners get a merit certificate.
  • You will get Individual Video Support, Group Video Support, Email Support, and Forum Support to clear your queries and doubts.
  • Real-time industry-relevant projects will make your learning purposeful.

Career Opportunities after Taking This Course

Taking this course would open up a plethora of career opportunities. According to AmbitionBox, the average salary of a Machine learning engineer is 7.5 LPA. With knowledge and skill gained through this AI ML course online, you can earn like other ML Engineers. Some positions that you can work for include,

  • Machine Learning Engineer: The role of an ML Engineer is to develop and train AI software and Machine Learning systems.
  • Data Scientists: Data Scientists work over structured and unstructured data to convert it into key actionable insights for organisations.
  • AI Engineer: The role of the AI Engineer is to build AI models that would help enterprises understand results better.

FAQs on Machine Learning Fundamentals In Depth

  1. Who can take up AI ML courses online?

Students and graduates with a technical background in Computer Science can opt for this course.

  1. Is this an online AI & ML course?

Yes, this is a 100% online course.

  1. What is AI & ML?

Artificial Intelligence is involved in making systems that can work like humans. Machine Learning is a subset of AI where the machine is allowed to learn on its own from provided data sets.

  1. What is the fee for this AI ML course?

The AI and machine learning course fee structure is flexible, and you can choose a plan that suits you. The basic plan would give you two months of access, the pro plan would give you four months of access, and the premium plan would provide you with lifetime access.

  1. How much can a Machine Learning Engineer earn?

According to AmbitionBox, the average salary of a Machine learning engineer is 7.5 LPA. After completing this course, you can earn this average pay and expect more once you become an experienced professional.

  1. Is there any certificate for completing this Machine Learning Fundamentals In Depth course?

Yes, after completing this best AI ML course, you shall be given a course completion certificate. The top 5% of the scorers shall be given a merit certificate alongside the course completion certificate.

  1. Is there any technical support for this AI ML course to clear doubts?

Yes, you can clear your queries with email and forum support.

Flexible Pricing

Talk to our career counsellors to get flexible payment options.

Premium

INR 45,000

Inclusive of all charges


Become job ready with our comprehensive industry focused curriculum for freshers & early career professionals

  • 1 Year Accessto Skill-Lync’s Learning Management System (LMS)

  • Personalized Pageto showcase Projects & Certifications

  • Live Individual & Group Sessionsto resolve queries, Discuss Progress and Study Plans.

  • Personalized & Hands-OnSupport over Mail, Telephone for Query Resolution & Overall Learner Progress.

  • Job-Oriented Industry Relevant Curriculumavailable at your fingertips curated by Global Industry Experts along with Live Sessions.

Instructors profiles

Our courses are designed by leading academicians and experienced industry professionals.

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1 industry expert

Our instructors are industry experts along with a passion to teach.

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8 years in the experience range

Instructors with 8 years extensive industry experience.

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Areas of expertise

  • Machine Learning
  • Deep Learning

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