Machine Learning

COURSE INTRODUCTION

Machine learning is taking over the world, and with that, there is a growing need among companies for professionals to know the ins and outs of machine learning

The machine learning market size is expected to grow from USD 1.03 Billion in 2016 to USD 8.81 Billion by 2022, at a Compound Annual Growth Rate (CAGR) of 44.1% during the forecast period

Simplilearn’s Machine Learning course will make you an expert in machine learning, a form of artificial intelligence that automates data analysis to enable computers to learn and adapt through experience to do specific tasks without explicit programming. You'll master machine learning concepts and techniques including supervised and unsupervised learning, mathematical and heuristic aspects, and hands-on modeling to develop algorithms and prepare you for the role of a Machine Learning Engineer.

KEY FEATURES

  • 44 hours of instructor-led training with certification
  • Gain expertise with 25+ hands-on exercises
  • 4 real-life Industry projects with integrated labs 
  • Lifetime access to self-paced learning
  • Dedicated mentoring session from our faculty of industry experts
  • 24*7 support with dedicated project mentoring sessions

COURSE OBJECTIVES

After finish the course, student will have knowledge and skills to:

  • Master the concepts of supervised and unsupervised learning, recommendation engine, and time series modelling
  • Gain practical mastery over principles, algorithms, and applications of machine learning through a hands-on approach that includes working on four major end-to-end projects and 25+ hands-on exercises
  • Acquire thorough knowledge of the statistical and heuristic aspects of machine learning
  • Implement models such as support vector machines, kernel SVM, naive Bayes, decision tree classifier, random forest classifier, logistic regression, K-means clustering and more in Python
  • Validate machine learning models and decode various accuracy metrics. Improve the final models using another set of optimization algorithms, which include Boosting & Bagging techniques
  • Comprehend theoretical concepts and how they relate to the practical aspects of machine learning

AUDIENCE

  • Developers aspiring to be data scientists or machine learning engineers
  • Analytics managers who are leading a team of analysts
  • Business analysts who want to understand data science techniques
  • Information architects who want to gain expertise in machine learning algorithms
  • Analytics professionals who want to work in machine learning or artificial intelligence
  • Graduates looking to build a career in data science and machine learning
  • Experienced professionals who would like to harness machine learning in their fields to get more insights

 

EXAM & CERTIFICATION

Unlock Simplilearn certificate

Online Classroom:

  • Attend one complete batch
  • Submit at least one completed project.

Online Self-Learning:

  • Complete 85% of the course
  • Submit at least one completed project.

Who provides the certificate?

Upon successful completion of this course, Simplilearn will provide you with an industry-recognized course completion certificate which has a lifelong validity.

COURSE CONTENTS

Lesson 1: Introduction to Artificial Intelligence and Machine Learning

Lesson 2: Techniques of Machine Learning

Lesson 3: Data Preprocessing

Lesson 4: Math Refresher

Lesson 5: Regression

Lesson 6: Classification

Lesson 7: Unsupervised learning - Clustering

Lesson 8: Introduction to Deep Learning

Practice Projects

CÓ THỂ BẠN QUAN TÂM
Array
(
)