What is a Machine Learning course?

It teaches how to build algorithms that learn from data and make predictions.

Do I need programming experience?

Basic Python knowledge is usually required or taught in beginner courses.

Is math required for ML?

Yes, understanding basic statistics, linear algebra, and probability helps.

What tools will I learn?

You'll use tools like Python, Scikit-learn, TensorFlow, Keras, and Jupyter.

What topics are covered?

Supervised and unsupervised learning, regression, classification, clustering, and model evaluation.

Are there hands-on projects?

Yes, most courses include real-world projects to apply what you learn.

What is a Machine Learning course?

It teaches how to build algorithms that learn from data and make predictions.

Do I need programming experience?

Basic Python knowledge is usually required or taught in beginner courses.

Is math required for ML?

Yes, understanding basic statistics, linear algebra, and probability helps.

What tools will I learn?

You'll use tools like Python, Scikit-learn, TensorFlow, Keras, and Jupyter.

What topics are covered?

Supervised and unsupervised learning, regression, classification, clustering, and model evaluation.

Are there hands-on projects?

Yes, most courses include real-world projects to apply what you learn.

Machine Learning Training Program

Name: Machine Learning Training Program
Item: Machine Learning Training Program
Rating: 4.80

Home /Data Science & AI/ Machine Learning Training Program

Learn the fundamental concepts of ML in this machine learning program. Enroll today to learn from a competent ML expert.

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Machine Learning Training Program

Machine learning is important because it gives enterprises a view of trends in ustomer behavior and business operational patterns, as well as supports the development of new products. Many of today's leading companies, such as Facebook, Google and Uber, make machine learning a central part of their operations

In this program you will learn:

Introduction to Machine Learning

Techniques of Machine Learning

Regression

Classification

Unsupervised Learning: Clustering

Distribution Clustering

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Introduction to Machine Learning

Articial Intelligence

Machine Learning

Machine Learning Algorithms

Algorithmic models of Learning

Applications of Machine Learning

Large Scale Machine Learning

Computational Learning theory

Reinforcement Learning

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Techniques of Machine Learning

Supervised Learning

Unsupervised Learning

Semi-supervised and Reinforcement Learning

Bias and variance Trade-off

Representation Learning

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Regression

Regression and its Types

Logistic Regression

Linear Regression

Polynomial Regression

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Classification

Meaning and Types of Classification

Nearest Neighbor Classifiers

K-nearest Neighbors

Probability and Bayes Theorem

Support Vector Machines

Naive Bayes

Decision Tree Classifier

Random Forest Classifier

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Unsupervised Learning: Clustering

About Clustering

Clustering Algorithms

K-means Clustering

Machine Learning Training Curriculum

Hierarchical Clustering

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Model optimization and Boosting

Ensemble approach

K-fold cross validation

Grid search cross validation

Ada boost and XG Boost

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+ More Lessons

Course Design By

Nasscom & Wipro

Course Offered By

Croma Campus

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Course Duration

45 Hrs.

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Flexible Batches For You

29-Nov-2025*
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01-Dec-2025*
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03-Dec-2025*
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Mor | Aft | Eve - Slot

29-Nov-2025*
Weekend

SAT - SUN

Mor | Aft | Eve - Slot

01-Dec-2025*
Weekday

MON - FRI

Mor | Aft | Eve - Slot

03-Dec-2025*
Weekday

MON - FRI

Mor | Aft | Eve - Slot

Course Price :

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