courseimg-38

Machine Learning Certification Course

intgateway
Last Update January 10, 2022
5.0 /5
(2)
3 already enrolled

About This Course

Ensure career success with this Machine Learning course. Learn this exciting branch of Artificial Intelligence with a program featuring 58 hrs of Applied Learning, interactive labs, 4 hands-on projects, and mentoring. With our Machine Learning training, master Machine Learning concepts are required for a Machine learning certification. This Machine Learning online course will provide you with the skills needed to become a successful Machine Learning Engineer today.

 

Machine Learning Course Overview

This Machine Learning course offers an in-depth overview of Machine Learning topics including working with real-time data, developing algorithms using supervised & unsupervised learning, regression, classification, and time series modeling. Learn how to use Python in this Machine Learning certification training to draw predictions from data.

 

Benefits

The Machine Learning market is expected to reach USD $30.64 Billion by 2024, at a Compound Annual growth rate(CAGR) of 42.8-percent, indicating the increased adoption of Machine Learning among companies. By 2024, the demand for Machine Learning engineers is expected to grow by 11-percent.

 

Machine Learning Course Curriculum

 

Eligibility

The Machine Learning certification course is well-suited for participants at the intermediate level including, Analytics Managers, Business Analysts, Information Architects, Developers looking to become Machine Learning Engineers or Data Scientists, and graduates seeking a career in Data Science and Machine Learning.

Pre-requisites

This Machine Learning course requires an understanding of basic statistics and mathematics at the college level. Familiarity with Python programming is also beneficial. Before getting into the Machine Learning certification training, you should understand these fundamental courses, including Python for Data Science, Math Refresher, and Statistics Essential for Data Science.

Course Content

Lesson 01 Course Introduction
Lesson 02 Introduction to AI and Machine Learning
Lesson 03 Data Preprocessing
Lesson 04 Supervised Learning
Lesson 05 Feature Engineering
Lesson 06 Supervised Learning Classification
Lesson 07 Unsupervised Learning
Lesson 08 Time Series Modeling
Lesson 09 Ensemble Learning
Lesson 10 Recommender Systems
Lesson 11 Text Mining
Lesson 12 Project Highlights
Practice Projects

 

Machine Learning Training FAQs

What is Machine Learning?
Machine learning is nothing but an implementation of Artificial Intelligence that allows systems to simultaneously learn and improve from past experiences without the need of being explicitly programmed. It is a process of observing data patterns, collecting relevant information, and making effective decisions for a better future of any organization. Machine learning facilitates the analysis of huge quantities of data, usually delivering faster and accurate results to extract profitable benefits and opportunities.

 

What is Machine Learning used for?
Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it to learn for themselves.

 

What are the different types of Machine Learning?
Machine learning is generally divided into three types – Supervised Learning, Unsupervised Learning, and Reinforcement Learning. This Machine Learning course gives you an in-depth understanding of all these three types of machine learning.

 

Does Machine Learning require coding?
Yes, some coding knowledge is required to perform certain machine learning tasks like statistical analysis. Basic knowledge of either Python, R, or Java is recommended before taking this Machine Learning certification course.

 

Is Machine learning a good career?
Machine learning is one of the most in-demand career fields today. Present-day applications like driverless cars, facial recognition, voice assistants, and ecommerce recommendation engines are powered by machine learning. This field will be relevant going forward and professionals entering it can fetch lucrative salaries. As a first step, you can take our machine learning online course and learn everything from scratch.

 

How do beginners learn Machine Learning?
Machine learning is in high demand. But before you jump into certification training, it’s essential for beginners to get familiar with the basics of machine learning first. Intelligence Gateway’s free resources articles, tutorials, and YouTube videos will help you get a handle on the concepts and techniques of machine learning. Start your learning with our free ML courses that serve as a foundation for this exciting and dynamic field: Statistics Essentials for Data Science, Math Refresher, and Data Science with Python.

 

What is the best language for Machine Learning?
Machine Learning Engineers take into account various factors to decide which language would best suit their project. Their top choices include Python, C++, R, Java, and JavaScript.

 

Are Machine Learning certifications worth it?
Having a Machine Learning certification will help you gain the necessary knowledge and training to shape your career in an AI-led future and deal with machine learning problems.

 

What are the job roles available after getting a Machine Learning certification?
Some of the top job roles in the field of Machine Learning are Data Scientist, Machine Learning Engineer, NLP Scientist, Computer Vision Engineer, and Data Architect. This Machine Learning course gives you all the necessary skills to become eligible for such roles.

 

What is the career exposure after completing this Machine Learning course?
Machine learning has gained global traction and many are aspiring to start a career in this field. Jobs in AI and machine learning have grown around 75 percent over the past few years and Gartner predicts that there will be 2.3 million jobs in the field by 2022. Our ML course will give you all the necessary skills to work in this exciting field.

 

What does a Machine Learning Engineer do?
The roles and responsibilities of Machine Learning Engineers include:

  • Designing and building machine learning systems and schemes
  • Analyzing and processing data science prototypes
  • Performing statistical analysis and modifying models using test results
  • Training ML systems whenever required and enhancing prevailing Machine Learning frameworks and libraries
  • Exploring new data to improve the machine’s performance

 

What skills should a Machine Learning Engineer know?
A Machine Learning Engineer is expected to be skilled in areas like core math, statistics, basic programming, data modeling, neural networks, natural language processing, ML tools and libraries, and more. Our Machine Learning course will impart all of these skills and make you job-ready.

 

What is the difference between Machine Learning and Deep Learning?

  • Machine learning is a subtype of Artificial Intelligence, while deep learning is the evolved version of machine learning.
  • Deep learning is driven by neural networks that imitate neurons in the human brain, embedding a multi-layer architecture. In contrast, machine learning involves the usage of statistical methods to make a machine learn automatically through previously stored data patterns and without the requirement of programming or any human intervention.

 

What is the difference between Machine Learning and Artificial Intelligence?
Artificial Intelligence is a broad field that encompasses everything that involves giving machines human-like intelligence. Machine learning is an important subset of AI where machines are given a lot of input data and algorithms are applied to train it and give them the ability to ‘learn’ and perform the desired actions. Our ML course deals with this topic in detail.

 

Will this ML course help me to build a successful career in Machine Learning?
Intelligence Gateway’s Machine Learning certification course is designed by subject matter experts who know what skills are most valued by employers. Topics like types of machine learning, time series modeling, regression, classification, clustering, and deep learning basics are thoroughly covered, and allow you to start a career in this field.

 

Is a Machine Learning course difficult to learn?
Intelligence Gateway’s machine learning course enables you to learn all the machine learning concepts systematically. The course is easy to understand and allows you to align theoretical knowledge with practical knowledge related to Machine learning. This is the best course for machine learning well suited for the ones who have prior knowledge of Statistics, Mathematics, Python programming and want to explore career options in machine learning.

 

What industries use Machine Learning most?
Industries that use machine learning extensively are transportation, healthcare, finance, agriculture, retail, and customer service. By pursuing the right Machine learning course, you can easily find jobs in these industries and have a highly fulfilling career ahead of you.

 

Which companies hire Machine Learning Engineers?
Companies commonly hire engineers with machine learning certifications are Amazon Web Services, Databricks, Dataiku, Google Cloud, IBM, MathWorks, Microsoft Azure, RapidMiner, SAS, and TIBCO.

 

What is the pay scale of Machine Learning professionals across the world?
Professionals with machine learning certification earn an average salary of $113,425 in a year.

 

Learning Objectives

Supervised and unsupervised learning
Time series modeling
Linear and logistic regression
Kernel SVM
KMeans clustering
Naive Bayes
Decision tree
Random forest classifiers
Boosting and Bagging techniques
Deep Learning fundamentals

Your Instructors

intgateway

4.81/5
163 Courses
32 Reviews
395 Students
See more

Student Feedback

5.0
2 Ratings
100%
0%
0%
0%
0%

Reviews (2)

this course is very helpful for me

Very good

Write a review

Free
Level
All Levels
Duration 58 hours
Language
English

Material Includes

  • Supervised and unsupervised learning
  • Time series modeling
  • Linear and logistic regression
  • Kernel SVM
  • KMeans clustering
  • Naive Bayes
  • Decision tree
  • Random forest classifiers
  • Boosting and Bagging techniques
  • Deep Learning fundamentals
Select the fields to be shown. Others will be hidden. Drag and drop to rearrange the order.
  • Image
  • SKU
  • Rating
  • Price
  • Stock
  • Availability
  • Add to cart
  • Description
  • Content
  • Weight
  • Dimensions
  • Additional information
  • Attributes
  • Custom attributes
  • Custom fields
Click outside to hide the compare bar
Compare
Wishlist 0
Open wishlist page Continue shopping