Introduction to Machine Learning Training

Bring innovation in the AI industry with Intro to Machine Learning course.

View Schedule Enquire Now
Course Image

12000+

Trained

20+

Data Scientist

4.6

rating

Overview

The introduction to machine learning course provides you basic understanding of AI models, logistic regression, multilayer perceptrons, convolutional neural networks, natural language processing, etc., along with their demonstration as to how they solve intricate problems across industries, be it image recognition or text prediction.

Experience the Machine Learning Training with practice exercises providing you the best experience in order to implement data science models on data sets. Learn how to apply machine learning algorithms with PyTorch, open-source libraries used by most prestigious companies in the industry.

Key Features of the course

26 hours of Interactive Learning

Learn from our experts who are also industry experts

Intermediate Level

Easy to learn course with flexible training methods

Increased Hireability

Boost your career by getting hired by top companies

Relevant Study Material

Get relevant study material designed by industry experts

Extensive Learning

Learn better with case studies, activities and quizzes

Comprehensive Learning

Understand the core concepts of Machine Learning

Curriculum

Topics Covered

  • Basics of Machine Learning
    • Learn the application of Machine Learning in Science and Technology
  • Naive Bayes
    • Learn to use Naive Bayes with Scikit learn in Python
    • Segregate data amongst training sets and testing sets with Scikit learn
  • Facilitate Vector Machines
    • Learn the Vector Machine mechanism
    • Understand how to choose the right kernel for SVM
    • Discover RBF and Linear Kernels
  • Decision Trees
    • Code your own decision tree in Python
    • Learn to calculate formulas for entropy and information gain
    • Identify email authors by using decision tree in Python
  • Algorithm
    • Explore how to choose the relevant Machine Learning Algorithm in K-Means, Adaboost, and Decision Trees
  • Datasets and Questions
    • Identify patterns in Enron Email Dataset
    • Understand how to identify fraud with case-study
  • Regressions
    • Differentiate between Continuous supervised learning and discrete learning
    • Code a Linear Regression in Python with scikit-learn
    • Familiarize yourself with various error metrics like SSE, R Squared in Linear Regression
  • Outliners
    • Eliminate outliers for the improvement of linear regression predictions quality
    • Discard the residuals on a real dataset, reimplementing the regressor
    • Apply the knowledge of outliers and residuals on the Enron Email Corpus
  • Clustering
    • Differentiate Unsupervised Learning from Supervised Learning
    • Apply K-Means in Python and find cluster center with Scikit Learn
    • Find clusters in a real dataset with Enron Finance Data
  • Feature Scaling
    • Learn how to improve algorithms by preprocess data with feature scaling
    • Use a min MX Scaler in sklearn

Prerequisite

  • This course doesn’t require any prior experience in Machine Learning. However, proficiency at programming in Python, basic stats and basic knowledge of Data Science would be beneficial.

What does Xebia provide differently?

Step into the realm of learning for an all-inclusive growth. Xebia is a pioneering IT consultancy and service provider that aims at Enterprise Development, Agile Development, DevOps, and Outsourcing Services.

World-class Training

World-class Training

Xebia Academy offers an intensive learning program and industry-specific training courses. It’s a globally acclaimed APMG International Partner for Big Data & Data Science training and certification courses. ReadmoreReadless

Boon To Career

Boon To Career

Xebia offers excellent consultancy, innovative tools, and continuous career growth. We will train you to become a Big Data and Data Science expert. ReadmoreReadless

Expert Advantage

Expert Advantage

Get trained by our In-House Data Science experts with an average of 18 years of experience: Data Science and Big Data Experts with extensive knowledge of data and AI.ReadmoreReadless

Flexible Learning

Flexible Learning

Pick the right course: You can choose a public class at our training centre, or learn with your colleagues in a customized, in-company training program, facilitated on-site at your location, anywhere in the world.ReadmoreReadless

Global Experience

Global Experience

18 years of professional training experience and trusted by over 1,00,000 professionals worldwide. Xebia Academy is the largest producer of Big Data and Data Science certifications globally.ReadmoreReadless

Global Experience

Hands-on And Practical Learning Experience

Our trainers are hands-on Data Science practitioners and provide interactive training sessions which let students master required skills in real-world scenarios, giving them an edge in the industry.ReadmoreReadless

Certification Process

  • 01

    Enroll for Introduction to Machine Learning course

  • 02

    Attend the Machine Learning Training

  • 03

    Get certified as an AI professional

Industry Connect

Who should attend this course?

People who usually take this course include:

  • Developers

  • Analytics Managers

  • Information Architects

  • Analytics Professionals

  • Graduates seeking AI career

What skills will you learn in the course?

Scope of Artificial Intelligence

Understand the meaning, scope and purpose of Artificial Intelligence and its impactsReadmoreReadless

Build your intelligent agents

Design your intelligent agents and apply them to make empirical AI projects ReadmoreReadless

Python Programming

Grasp the key concepts of Python programming, data types, tuples, lists, dicts, basic operators and functions ReadmoreReadless

Data Science processes

Gain a profound understanding of Data Science processes: data wrangling, sata exploration, data visualization, hypothesis building, and testingReadmoreReadless

Learning Models

Understand the concepts of supervised and unsupervised learning models that include Linear Regression, Logistic Regression, Clustering, Dimensionality Reduction, K-NN and Pipeline, Recommendation Engine and Time Series Modelling. ReadmoreReadless

Advanced Concepts

Master the advanced concepts of Artificial Intelligence such as, neutral neurals, recurrent neural networks, training deep networks, and high-level interfaces.ReadmoreReadless

Why should you attend this course?

With the exponential rise of Artificial Intelligence in the world, the demand of a Machine Learning professional/AI Engineer is and will be on a rise. Machine learning has made its place in our personal lives with advanced technologies as well as in industries like Pharmaceuticals, Banks and Financial Services, Health Care, Online Sales, Retail, Government Schemes, Space exploration and Science Studies, the opportunity to land a job across industries becomes easy.

  • Get noticed by Corporate Giants who have incorporated AI till their cores
  • Discover new concepts and be a part of innovative projects
  • Bring transformation in your enterprise

Know your Trainers

Program Visual Library

FAQs

Since Machine Learning is adapted in every aspect of lives, businesses and industries. Industries like Pharmaceuticals, Banking, Health Care, E-Commerce, Intelligence, Space and Science Studies etc.

Almost every industry possible has adapted Machine learning due to its service and effectiveness. So one can get job opportunities across industries with its expanding scope.

By the end of the course you’ll be able to:

  • Understand the meaning, scope and impact of Artificial Intelligence with advanced concepts
  • Design your intelligent agents and apply them to make empirical AI projects Grasp the key concepts of Python programming
  • Gain a profound understanding of Data Science processes: data wrangling, sata exploration, data visualization, hypothesis building, and testing
  • Understand the concepts of supervised and unsupervised learning models

This course doesn’t require any prior experience in Machine Learning. However, if you have proficiency at programming in Python, basic stats and basic knowledge of Data Science that would be beneficial.

People who attend this course are:

  • Developers
  • Analytics Managers
  • Information Architects
  • Analytics Professionals
  • Graduates seeking AI career

The courses are taught by industry experts who provide up-to-date information and train in a flexible way with interactive discussions and sessions. Our trainers make sure that each and every student is learning to their full potential.

Sure. This course is specifically designed for beginners, so that they can kick start their careers.

Library Image

Repositories of trending knowledge

Knowledge sources from Xebians to enlighten learners

View More
  • Library Image
  • Library Image
  • Library Image
  • Library Image

Stay updated about the latest courses

Register now to receive notifications of upcoming trainings and latest courses.