Overview of Course

Machine Learning Training is a comprehensive course designed to provide you with a strong foundation in the field of machine learning. This course covers everything from the basics to advanced topics, including supervised and unsupervised learning, data preprocessing, feature engineering, model selection, and more.

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Course Highlights

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Hands-on experience with real-world datasets

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Practical assignments to reinforce learning

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Expert-led online sessions

Key Differentiators

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    Personalized Learning with Custom Curriculum

    Training curriculum to meet the unique needs of each individual

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    Trusted by over 100+ Fortune 500 Companies

    We help organizations deliver right outcomes by training talent

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    Flexible Schedule & Delivery

    Choose between virtual/offline with Weekend options

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    World Class Learning Infrastructure

    Our learning platform provides leading virtual training labs & instances

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    Enterprise Grade Data Protection

    Security & privacy are an integral part of our training ethos

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    Real-world Projects

    We work with experts to curate real business scenarios as training projects

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Skills You’ll Learn


Data preprocessing and feature engineering


Model selection and hyperparameter tuning


Supervised and unsupervised learning


Regression and classification


Neural networks and deep learning

Training Options

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1-on-1 Training

USD 3400 / INR 280000
  • Option Item Access to live online classes
  • Option Item Flexible schedule including weekends
  • Option Item Hands-on exercises with virtual labs
  • Option Item Session recordings and learning courseware included
  • Option Item 24X7 learner support and assistance
  • Option Item Book a free demo before you commit!
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Corporate Training

On Request
  • Option Item Everything in 1-on-1 Training plus
  • Option Item Custom Curriculum
  • Option Item Extended access to virtual labs
  • Option Item Detailed reporting of every candidate
  • Option Item Projects and assessments
  • Option Item Consulting Support
  • Option Item Training aligned to business outcomes
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Course Reviews


  • Basic Syntax and Data Types
  • Control Statements and Loops
  • Functions and Modules
  • Object-Oriented Programming
  • File Input and Output
  • Exception Handling

  • What is Anaconda Navigator
  • Download and Installation
  • Using Anaconda Navigator
  • Managing Packages with Anaconda

  • Introduction to Machine Learning
  • Types of Machine Learning
  • Applications of Machine Learning
  • Advantages and Disadvantages of Machine Learning
  • Machine Learning Workflow

  • What is Artificial Intelligence
  • Types of Artificial Intelligence
  • Applications of Artificial Intelligence
  • Advantages and Disadvantages of Artificial Intelligence
  • Future of Artificial Intelligence

  • Types of Graphical Models
  • Bayesian Networks
  • Markov Networks
  • Applications of Graphical Models
  • Learning with Graphical Models

  • Probability Theory
  • Descriptive Statistics
  • Inferential Statistics
  • Probability Distributions
  • Statistical Inference

  • Introduction to Data Pre-Processing
  • Data Cleaning
  • Data Transformation
  • Feature Scaling
  • Data Integration and Reduction

  • Supervised Learning
  • Unsupervised Learning
  • Semi-Supervised Learning
  • Reinforcement Learning
  • Deep Learning

  • Introduction to KNN
  • KNN Algorithm
  • Choosing the Value of K
  • Distance Metrics
  • Applications of KNN

  • Introduction to Decision Trees
  • Decision Tree Learning Algorithm
  • Overfitting and Pruning
  • Handling Missing Values
  • Applications of Decision Trees

  • Introduction to Support Vector Machines
  • SVM Algorithm
  • Kernel Functions
  • Soft Margin SVM
  • Applications of SVM

  • Introduction to Clustering
  • Hierarchical Clustering
  • K-Means Clustering
  • DBSCAN Clustering
  • Evaluation of Clustering Results

  • Introduction to Artificial Neural Networks
  • Perceptrons
  • Multilayer Neural Networks
  • Backpropagation Algorithm
  • Applications of ANN

  • Introduction to Natural Language Processing
  • Text Pre-Processing
  • Language Modeling
  • Text Classification
  • Sentiment Analysis

  • Introduction to Reinforcement Learning
  • Markov Decision Processes
  • Q-Learning Algorithm
  • Policy Gradient Methods
  • Applications of Reinforcement Learning
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Inquiry for :


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Target Audience:

  • Software engineers
  • Data analysts
  • Data scientists
  • IT professionals
  • Anyone interested in learning machine learning
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  • Basic knowledge of programming and statistics
  • Familiarity with Python programming language
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Benefits of the course:

  • Gain a comprehensive understanding of machine learning concepts and techniques
  • Acquire hands-on experience with real-world datasets
  • Enhance your career prospects by adding machine learning skills to your resume
  • Get certified on successful completion of the course
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Exam details to pass the course:

  • Online examination at the end of the course
  • Minimum passing score of 70%
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Certification path:

  • Skillzcafe Machine Learning Training Certificate
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Career options:

  • Machine learning engineer
  • Data scientist
  • Business analyst
  • Data analyst
  • Artificial intelligence engineer

Why should you take this course from Skillzcafe:

Why should you take this course from Skillzcafe:
  • Bullet Icon Expert-led training with industry professionals
  • Bullet Icon Hands-on experience with real-world datasets
  • Bullet Icon Practical assignments to reinforce learning
  • Bullet Icon Lifetime access to course materials
  • Bullet Icon Certification on successful completion of the course


The course duration is 54 hours.

The course is primarily taught using Python.

Yes, this course is suitable for beginners as well as experienced professionals.

The course uses real-world datasets from various industries.

Yes, you will receive a Skillzcafe Machine Learning Training Certificate on successful completion of the course.

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