• star

    4.6

  • star

    4.89

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    4.94

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    4.7

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    4.6

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    4.89

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University Programs

UNIVERSITY
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Great Learning

12 weeks  • Online

UNIVERSITY
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Walsh College

2 Years  • Online

UNIVERSITY
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MIT Professional Education

14 Weeks  • Online

Learn from MIT Faculty
UNIVERSITY
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Johns Hopkins University

16 weeks  • Online

Free Model Evaluation Courses

FREE
Introduction to Machine Learning
star   4.46 78.1K+ Learners 1 hr

Skills: Learn the fundamentals of machine learning, including supervised and unsupervised learning, regression, and recommendation systems. Join this free machine learning course to apply these skills in real-world business scenarios.

FREE
Python for Machine Learning
star   4.51 475.7K+ Learners 1.5 hrs

Skills: NumPy Arrays, NumPy Operations, NumPy Math, Saving & Loading NumPy, Pandas Series, Pandas DataFrame, Pandas Functions (Mean, Median, Max, Min), Data Manipulation, Supervised Learning, Unsupervised Learning, Machine Learning with Python

FREE
Supervised Machine Learning with Tree Based Models
star   4.56 9.9K+ Learners 2 hrs

Skills: Scikit Learn Library, Decision Tree, Random Forest, Demonstration for Algorithms

FREE
Supervised Machine Learning with Logistic Regression and Naïve Bayes
star   4.43 21.9K+ Learners 2 hrs

Skills: Scikit Learn Library,Logistic Regression, Naïve Bayes

FREE
Hierarchical Clustering
star   4.52 2.2K+ Learners 1 hr

Skills: Introduction to Hierarchical Clustering, Agglomerative Hierarchical Clustering, Euclidean Distance, Manhattan Distance, Minkowski Distance, Jaccard Index, Cosine Similarity, Optimal Number of Clusters

FREE
Feature Engineering
star   4.58 3.5K+ Learners 1.5 hrs

Skills: Process of feature engineering, Feature engineering techniques, Correlation matrix, Model performance analysis, Feature engineering demo using a real-life dataset

FREE
Machine Learning Modelling
star   4.62 4.9K+ Learners 2.5 hrs

Skills: Linear Regression, Logistic Regression, Naïve Bayes

FREE
k-fold Cross Validation
star   4.61 1.8K+ Learners 1 hr

Skills: Introduction to Cross Validation, Process of Cross Validation, Types of Cross Validation

FREE
Bias Variance Tradeoff
star   4.59 1.3K+ Learners 0.5 hr

Skills: Bias, Variance, Trade-off, How to avoid overfitting and underfitting?

free icon FREE
Introduction to Machine Learning
star   4.46 78.1K+ Learners 1 hr

Skills: Learn the fundamentals of machine learning, including supervised and unsupervised learning, regression, and recommendation systems. Join this free machine learning course to apply these skills in real-world business scenarios.

free icon FREE
Python for Machine Learning
star   4.51 475.7K+ Learners 1.5 hrs

Skills: NumPy Arrays, NumPy Operations, NumPy Math, Saving & Loading NumPy, Pandas Series, Pandas DataFrame, Pandas Functions (Mean, Median, Max, Min), Data Manipulation, Supervised Learning, Unsupervised Learning, Machine Learning with Python

free icon FREE
Supervised Machine Learning with Tree Based Models

Skills: Scikit Learn Library, Decision Tree, Random Forest, Demonstration for Algorithms

free icon FREE
Supervised Machine Learning with Logistic Regression and Naïve Bayes

Skills: Scikit Learn Library,Logistic Regression, Naïve Bayes

free icon FREE
Hierarchical Clustering
star   4.52 2.2K+ Learners 1 hr

Skills: Introduction to Hierarchical Clustering, Agglomerative Hierarchical Clustering, Euclidean Distance, Manhattan Distance, Minkowski Distance, Jaccard Index, Cosine Similarity, Optimal Number of Clusters

free icon FREE
Feature Engineering
star   4.58 3.5K+ Learners 1.5 hrs

Skills: Process of feature engineering, Feature engineering techniques, Correlation matrix, Model performance analysis, Feature engineering demo using a real-life dataset

free icon FREE
Machine Learning Modelling
star   4.62 4.9K+ Learners 2.5 hrs

Skills: Linear Regression, Logistic Regression, Naïve Bayes

free icon FREE
k-fold Cross Validation
star   4.61 1.8K+ Learners 1 hr

Skills: Introduction to Cross Validation, Process of Cross Validation, Types of Cross Validation

free icon FREE
Bias Variance Tradeoff
star   4.59 1.3K+ Learners 0.5 hr

Skills: Bias, Variance, Trade-off, How to avoid overfitting and underfitting?

Learner reviews of the Free Model Evaluation Courses

Our learners share their experiences of our courses

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Reviewer Profile

5.0

★★★★ ★
India
“My Experience is Wonderful. I Loved This Course ❤️❤️❤️”
I liked everything in the course. I enjoyed every video and gained good knowledge from all of them. I learned many things and cleared many doubts. Thank you so much 😊
Reviewer Profile

5.0

★★★★ ★
India
“Extremely Easy and Perfect for Beginners!”
It was easy, and the teacher was skilled and explained everything in simple terms!
Reviewer Profile

5.0

★★★★ ★
India
“Great Experience Learning from a Great Resource Person”
It was a great experience to learn from such a great resource person. The instructor explained the entire concept beautifully, and I scored 5/5 on the first attempt.
Reviewer Profile

5.0

★★★★ ★
United Arab Emirates
“A Simple and Beginner-Friendly ML Course”
The course curriculum is structured such that beginners don't get overwhelmed by the vastness of the subject, yet it explains what to expect.
Reviewer Profile

5.0

★★★★ ★
India
“Gained Knowledge on Machine Interaction and Data Collection”
In machine learning, we see how machines collect data and, after analysis, provide more about our needs. I enjoyed the session and the interesting quizzes. It is full of interest and logic-based.
Reviewer Profile

4.0

★★★ ★ ☆
India
“Classification Model of Machine Learning”
In machine learning, classification is one of the most important topics, and I like this topic the most.
Reviewer Profile

5.0

★★★★ ★
India
“Machine Learning (ML) as a Subset of Artificial Intelligence (AI)”
Machine Learning (ML) is a subset of artificial intelligence (AI) that enables systems to learn and make decisions or predictions based on data without being explicitly programmed.
Reviewer Profile

5.0

★★★★ ★
India
“Easy to Learn. Thank You for Such a Nice Free Course.”
I'm grateful for the effort you put into creating this valuable resource.
Reviewer Profile

5.0

★★★★ ★
India
“ML Tools and Workflow in AI Technology”
The machine learning workflow often involves evaluating the model's performance using metrics to determine how well it has learned from the training data and how effectively it can make predictions on new, unseen data.
Reviewer Profile

5.0

★★★★ ★
India
“Good and Informative Experience”
This course, Introduction to Machine Learning, gave me a good introduction to machine learning, which is quite informative and interesting.

Meet your faculty

Meet industry experts who will teach you relevant skills in Model Evaluation

instructor img

Dr. Abhinanda Sarkar

Senior Faculty & Director Academics, Great Learning
  • ◆
    30+ years of experience in data science, ML, and analytics.
  • ◆
    Ph.D. from Stanford, taught at MIT, ISI, and IIM Bangalore.
instructor img

Mr. Bharani Akella

Data Scientist
Bharani has been working in the field of data science for the last 2 years. He has expertise in languages such as Python, R and Java. He also has expertise in the field of deep learning and has worked with deep learning frameworks such as Keras and TensorFlow. He has been in the technical content side from last 2 years and has taught numerous classes with respect to data science.