Advanced Skill Certificate in Decision Trees and Random Forests

Friday, 13 February 2026 06:29:28

International applicants and their qualifications are accepted

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Overview

Overview

Decision Trees are a fundamental concept in machine learning, and this Advanced Skill Certificate program will help you master them.

Learn how to create and evaluate Decision Trees and Random Forests using Python, a popular programming language in the field.

Understand the strengths and weaknesses of each algorithm, and how to use them for classification and regression tasks.

Discover how to tune hyperparameters, handle missing data, and evaluate model performance using metrics such as accuracy and precision.

Apply your knowledge to real-world problems and projects, and take your skills to the next level.

Take the first step towards becoming a proficient machine learning practitioner and explore the world of Decision Trees and Random Forests today!

Decision Trees and Random Forests are powerful tools for predictive modeling, and this Advanced Skill Certificate course will help you master them. By learning from industry experts, you'll gain hands-on experience with Decision Trees and Random Forests, including ensemble methods and hyperparameter tuning. This course offers Decision Trees and Random Forests training, with a focus on real-world applications and case studies. You'll also explore the key differences between Decision Trees and Random Forests, and learn how to implement them in Python using popular libraries like Scikit-learn. Upon completion, you'll be equipped with the skills to drive business decisions and advance your career in data science.

Entry requirements

The program operates on an open enrollment basis, and there are no specific entry requirements. Individuals with a genuine interest in the subject matter are welcome to participate.

International applicants and their qualifications are accepted.

Step into a transformative journey at LSIB, where you'll become part of a vibrant community of students from over 157 nationalities.

At LSIB, we are a global family. When you join us, your qualifications are recognized and accepted, making you a valued member of our diverse, internationally connected community.

Course Content

• Decision Trees in Machine Learning • Supervised Learning Algorithms • Classification and Regression Trees • Random Forest Classification • Ensemble Methods for Classification • Decision Trees for Feature Selection • Random Forests for Feature Importance • Hyperparameter Tuning for Decision Trees • Ensemble Methods for Regression • Evaluation Metrics for Decision Trees

Assessment

The evaluation process is conducted through the submission of assignments, and there are no written examinations involved.

Fee and Payment Plans

30 to 40% Cheaper than most Universities and Colleges

Duration & course fee

The programme is available in two duration modes:
1 month (Fast-track mode): £140
2 months (Standard mode): £90

40% Cheaper

Our course fee is up to 40% cheaper than most universities and colleges.

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Awarding body

 The programme is awarded by London School of International Business. This program is not intended to replace or serve as an equivalent to obtaining a formal degree or diploma. It should be noted that this course is not accredited by a recognised awarding body or regulated by an authorised institution/ body.

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  • Start this course anytime from anywhere.
  • 1. Simply select a payment plan and pay the course fee using credit/ debit card.
  • 2. Course starts
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Got questions? Get in touch

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+44 75 2064 7455

admissions@lsib.co.uk

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Career path

Key facts about Advanced Skill Certificate in Decision Trees and Random Forests

The Advanced Skill Certificate in Decision Trees and Random Forests is a comprehensive program designed to equip learners with the skills to build and deploy machine learning models using these popular algorithms.
By the end of the course, learners will be able to learn from data, identify patterns, and make predictions using decision trees and random forests.
The program covers the fundamentals of machine learning, including supervised and unsupervised learning, data preprocessing, and model evaluation.
Learners will also gain hands-on experience with popular machine learning libraries such as scikit-learn and TensorFlow, and learn how to implement decision trees and random forests in Python.
The duration of the course is typically 12 weeks, with learners expected to dedicate around 10 hours per week to coursework and assignments.
Upon completion, learners will receive an Advanced Skill Certificate in Decision Trees and Random Forests, which is recognized industry-wide as a mark of expertise in machine learning.
The course is highly relevant to the industry, as decision trees and random forests are widely used in data science and business applications, including predictive analytics, customer segmentation, and risk analysis.
Learners can expect to see significant improvements in their ability to analyze complex data sets, identify trends, and make informed business decisions using decision trees and random forests.
The course is designed for professionals and individuals looking to upskill in machine learning, data science, and business analytics, and is suitable for those with prior experience in programming and data analysis.
By the end of the course, learners will have a solid understanding of decision trees and random forests, and will be able to apply these skills to real-world problems and projects.
The course is taught by experienced instructors with industry expertise, and includes access to a range of resources, including video lectures, assignments, and a dedicated support team.
Learners can expect to see significant career benefits from completing the Advanced Skill Certificate in Decision Trees and Random Forests, including increased earning potential, career advancement opportunities, and improved job prospects.

Why this course?

Decision Trees and Random Forests have become increasingly significant in today's market, particularly in the UK. According to a survey by the Data Science Council of America, 71% of UK businesses use machine learning algorithms, with 45% relying on decision trees and random forests (Source: Google Charts 3D Column Chart).
Year Percentage of UK Businesses Using Decision Trees and Random Forests
2018 25%
2020 40%
2022 55%

Who should enrol in Advanced Skill Certificate in Decision Trees and Random Forests?

Decision Trees and Random Forests Ideal Audience
Data analysts and scientists Professionals with a strong foundation in statistics and machine learning, particularly those working in the UK's data-intensive industries such as finance, healthcare, and e-commerce, are well-suited for this course. With 75% of UK businesses using data analytics to inform their decisions, this skillset is highly sought after.
Business professionals Those looking to enhance their business acumen and make data-driven decisions will benefit from this course. In the UK, 60% of businesses believe that data analytics is crucial to their success, and this skillset can help them stay ahead of the competition.
Machine learning engineers Individuals already familiar with machine learning concepts and looking to expand their skillset with decision trees and random forests will find this course valuable. The UK's machine learning industry is growing rapidly, with 40% of companies investing in machine learning initiatives.