Machine Learning Training & Certification Program

Post Graduate Program In AI And Machine Learning Course. Online and Offline Training

This course Learns how to deploy machine learning models using cloud computing with an advanced certification program. Our Certified Instructors learn this exciting branch of Artificial Intelligence with a program consisting of 60 hours of applied learning, interactive labs, 5 hands-on projects and mentoring.

This machine learning online training will give you the skills you need to become a successful machine learning engineer today.

4.9 Ratings on Reviews
10k+ Students Enrolled
Guarantee Success
Drop Your Query

💡 One among the top 10 most valuable certification

💡 90% of the people get job after Certification

💡 Experienced and Certified Trainers

About Program

Our Certified Trainers offers an in-depth overview of Machine Learning topics including Data Science working with real-time data, developing algorithms using supervised & unsupervised learning, regression, classification, and time series modeling in Machine Learning Courses. Learn how to use machine learning techniques by analyzing data and making predictions based on it.


  • Gain expertise with 25+ hands-on exercises
  • 20+ Case Studies and Projects
  • Dedicated mentoring sessions from industry experts
  • No Cost EMI Option
  • Practical Hands-on Workshops
  • Industry Readiness Assessments

Top Skills You Will Learn

  • Python
  • BD processing using Spark
  • Deploy ML Models
  • Supervised & Unsupervised ML Models
  • Predictive Analytics & Statistics


  • Big Data Analyst
  • Data Engineer
  • Data Scientist
  • Machine Learning Engineer
  • Machine Learning Engineer
  • Decision scientist

Machine Learning Course Overview

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.

Every industry makes data-driven decisions to reach their potential consumers/audiences to improve their business. Data Science uses machine learning techniques to analyze data and make predictions based on it. For example, you can use machine learning techniques to predict different sales for a business at more than one location.

In Data Science, we collect large chunks of data, filter/group them based on our need/application, and use math and statistics to see the patterns behind it. That way, we get the answers to the questions we need. Whereas, in machine learning, we use data for testing and training our models. It is all about building models that can learn from the given data and provide results or predictions based on recent trends.

Examples: recognizing fingerprints, estimating stock prices, and self-driving cars.


Course Curriculum

  • Python Programming
  • Python for Data Science
  • Installing Python
  • Data Visualisation
  • Python Assignment (Optional)

  • Exploratory Data Analysis and Data Visualisation
  • Intro to ML + Understanding the ML pipeline
  • Introduction to Cloud
  • Elastic Provision Services of Cloud and Setting up Cloud
  • Assignment

  • Introduction to HDFS
  • Introduction to SQL
  • Hive Querying
  • Case Study
  • Assignment

  • Introduction to Spark
  • PySpark Programming
  • PySpark implementation on a Dataset: ALS & Spark Streaming
  • Assignment

  • Inferential Statistics and Hypothesis Testing
  • Linear Regression - I
  • Linear Regression - II
  • Logistic Regression
  • Assignment

  • Decision Trees
  • Random Forest Trees
  • Assignment
  • Principal Component Analysis + Linear Algebra
  • Clustering

  • Introduction to Neural Nets with TensorFlow
  • Convolution Neural Networks
  • Melanoma Detection Assignment
  • Recurrent Neural Networks

  • Natural Language Processing Fundamentals
  • Case Study on applications of Deep Learning in NLP
  • Case Study on Computer Vision
  • NN Assignment: Gesture Recognition

  • Deployment
  • Implementation: Regression + Model Selection on SageMaker

  • Capstone Project

Request more information


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.

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.

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.

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.

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.

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. IRA Soft Consultancy Service 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.