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Machine Learning using Python

25 Hours
Online Instructor-led Training
USD 525
Machine Learning using Python course and certification
1 Learner

About this Course
Machine learning (ML) is a method of data analysis that automates analytical model building. It is a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention.
In this course you will learn all the concept of Machine learning from basic to advanced level using Python programming. At the end of this course you will also understand how to build a recommendation system.

Machine Learning using Python

Course Details & Curriculum

Machine Learning with Python Programming- syllabus


Introduction to Machine Learning

What is a Machine Learning?

Need for Machine Learning

Why & When to Make Machines Learn?

Challenges in Machines Learning

Application of Machine Learning

Types of Machine Learning

Types of Machine Learning

      Supervised learning

      Unsupervised learning

      Reinforcement learning

Difference between Supervised and Unsupervised learning


Components of Python ML Ecosystem

Using Pre-packaged Python Distribution: Anaconda

Jupyter Notebook




Regression Analysis (Part-I)

Regression Analysis

Linear Regression

Examples on Linear Regression

scikit-learn library to implement simple linear regression

Regression Analysis (Part-II)

Multiple Linear Regression

Examples on Multiple Linear Regression

Polynomial Regression

Examples on Polynomial Regression

Classification (Part-I)

What is Classification

Classification Terminologies in Machine Learning

Types of Learner in Classification

Logistic Regression

Example on Logistic Regression

Classification (Part-II)

What is KNN?

How does the KNN algorithm work?

How do you decide the number of neighbors in KNN?

Implementation of KNN classifier

What is a Decision Tree?

Implementation of Decision Tree

SVM and its implementation

Clustering (Part-I)

What is Clustering?

Applications of Clustering

Clustering Algorithms

K-Means Clustering

How does K-Means Clustering work?

K-Means Clustering algorithm example

Clustering (Part-II)

Hierarchical Clustering

Agglomerative Hierarchical clustering and how does it work

Woking of Dendrogram in Hierarchical clustering

Implementation of Agglomerative Hierarchical Clustering

Association Rule Learning

Association Rule Learning

Apriori algorithm

Working of Apriori algorithm

Implementation of Apriori algorithm

Recommender Systems

Introduction to Recommender Systems

Content-based Filtering

How Content-based Filtering work

Collaborative Filtering

Implementation of Movie Recommender System

Machine Learning using Python

After the completion of this course, you will get the certification.

Career Path

The market for Artificial Intelligence and Machine Learning is extremely hot right now. The demand for talented and skilled professionals in Machine Learning is at its peak now, and in the future, it will only escalate higher. The great thing about a Machine Learning career is that apart from job satisfaction and security, it also promises hefty annual compensation and fast career growth. All the more reason to consider building a Machine Learning career path. 

Once you have acquired the right ML skills, here are the top five promising Machine Learning career paths that you can aspire for:
1. Machine Learning Engineer
2. Data Scientist
3. Software Developer/Engineer (AI/ML)
4. Human-Centered Machine Learning Designer

Job Prospects

According to a 2019 Indeed report, Machine Learning Engineer is the #1 job in the list of The Best Jobs in the US, recording a whopping 344% growth with a median salary of $146,085 per year. In India, the national average salary for Machine Learning jobs is ₹11,05,748.

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