Data Mining & Machine Learning with R Training

Data Mining & Machine Learning with R

Unlock the combined power of Data Mining & Machine Learning using R in our intensive training. Dive deep into analytical techniques, leveraging R's robust packages and frameworks.

Designed for data scientists and analysts, this course offers a comprehensive walkthrough from basic regression to advanced multidimensional reduction techniques.

What will you learn?

Advance Your Skills in Data Mining & Machine Learning with R. Over this 2-day intensive course, participants will:

Embrace R’s Capabilities: Recognize R as a premier tool for statistical computing, data analysis, and visualization.
Grasp Core Concepts: Differentiate between statistical learning and machine learning, understand the bias-variance trade-off, and more.
Master Supervised Learning: Dive into techniques from linear regression to decision trees, enhancing predictive modeling skills.
Explore Unsupervised Learning: Understand the intricacies of clustering, its challenges, and explore methods beyond K-means.
Dive into Advanced Topics: Enhance predictions with ensemble models, boosting, and dive into dimensionality reduction techniques.By the end of this course, participants will have a solid foundation in both the theoretical and practical applications of data mining and machine learning using R.

Requirements:

Data Scientist Background: This course is tailored for those with prior knowledge in the Data Scientist skill set, particularly within the domain of Analytical Techniques and Methods.

Course Outline*:

*We know each team has their own needs and specifications. That is why we can modify the training outline per need.

1. Introduction to Data Mining & Machine Learning

Distinguishing Statistical Learning from Machine Learning
Essentials of Iteration and Evaluation
Navigating the Bias-Variance Trade-off

2. Regression Techniques

Fundamentals of Linear Regression
Exploring Generalizations and Non-linearities
Hands-on Exercises

3. Mastering Classification

Refresher on Bayesian Principles
Techniques: Naive Bayes to Neural Networks
Discriminant Analysis, Logistic Regression, and More
In-depth Exploration of Support Vector Machines and Decision Trees
Practical Exercises

4. Cross-validation and Resampling

Deep Dive into Cross-validation Techniques
Exploring the Bootstrap Method
Skill-building Exercises

5. Unsupervised Learning Adventures

Introduction to K-means Clustering
Delving into Real-world Examples
Challenges and Advanced Techniques Beyond K-means

6. Advanced Modeling Topics

Unraveling Ensemble and Mixed Models
Techniques in Boosting
Practical Application Examples

7. Exploring Multidimensional Reduction

Introduction to Factor Analysis
Delve into Principal Component Analysis
Hands-on Analytical Examples.

Hands-on learning with expert instructors at your location for organizations.

Level:

Intermediate

Duration:

Hours (days:

)

Training customized to your needs

Immersive hands-on experience in a dedicated setting

*Price can range depending on number of participants, change of outline, location etc.

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Master new skills guided by experienced instructors from anywhere.

Level:

Intermediate

Duration:

Hours (days:

)

Training customized to your needs

Reduced training costs

*Price can range depending on number of participants, change of outline, location etc.

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You can participate in a Public Course with people from other organisations.

/per trainee

Thanks for the numbers, they could be going to your emails. But they're going to mine... Thanks ;D

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Level:

Intermediate

Duration:

Hours (days:

)

Fits ideally for individuals and small groups

Networking opportunities with fellow participants.

*Price can range depending on number of participants, change of outline, location etc.

Get Quote

Data Mining & Machine Learning with R

What will you learn?

Requirements:

Course Outline*:

1. Introduction to Data Mining & Machine Learning

2. Regression Techniques

3. Mastering Classification

4. Cross-validation and Resampling

5. Unsupervised Learning Adventures

6. Advanced Modeling Topics

7. Exploring Multidimensional Reduction

Get Quote for:

Data Mining & Machine Learning with R

Start your training experience here!