Professional Certificate in Decision Trees and Random Forests in AI

Monday, 16 February 2026 02:29:45

International applicants and their qualifications are accepted

Start Now     Viewbook

Overview

Overview

Decision Trees are a fundamental concept in Artificial Intelligence (AI) and Machine Learning (ML). They enable data analysis and prediction by breaking down complex problems into simpler, more manageable parts.

Designed for professionals and enthusiasts alike, this Professional Certificate in Decision Trees and Random Forests in AI provides an in-depth understanding of these powerful algorithms.

Learn how to apply Decision Trees and Random Forests to real-world problems, including classification, regression, and feature selection.

Develop practical skills in data preprocessing, model evaluation, and hyperparameter tuning.

Gain a solid foundation in the theoretical aspects of Decision Trees and Random Forests, including bias-variance tradeoff and model interpretability.

Enhance your career prospects in data science, business intelligence, and related fields.

Start your journey in Decision Trees and Random Forests today and unlock the full potential of AI and ML.

Decision Trees and Random Forests are fundamental concepts in Artificial Intelligence (AI) that enable data-driven decision-making. This Professional Certificate course delves into the world of Decision Trees and Random Forests, providing a comprehensive understanding of these powerful algorithms. Learn how to build and train models, evaluate performance, and apply them to real-world problems. With this course, you'll gain Decision Trees and Random Forests expertise, enhancing your career prospects in data science, machine learning, and business intelligence. Key benefits include improved predictive modeling, enhanced data analysis, and increased business value.

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 • Random Forests for Classification • Ensemble Methods in AI • Feature Selection Techniques • Overfitting and Regularization • Decision Trees and Regression • Random Forests for Regression • Hyperparameter Tuning • Evaluation Metrics for 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.

Start Now

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.

Start Now

  • Start this course anytime from anywhere.
  • 1. Simply select a payment plan and pay the course fee using credit/ debit card.
  • 2. Course starts
  • Start Now
    •

Got questions? Get in touch

Chat with us: Click the live chat button

+44 75 2064 7455

admissions@lsib.co.uk

+44 (0) 20 3608 0144



Career path

Key facts about Professional Certificate in Decision Trees and Random Forests in AI

The Professional Certificate in Decision Trees and Random Forests in AI is a comprehensive program designed to equip learners with the skills needed to build and deploy machine learning models using decision trees and random forests.
This program is ideal for data scientists, analysts, and practitioners who want to enhance their knowledge of supervised learning techniques and improve their ability to make data-driven decisions.
Upon completion of the program, learners will be able to apply decision trees and random forests to real-world problems, including classification, regression, and feature selection tasks.
The program covers the fundamentals of decision trees, including tree pruning, boosting, and bagging, as well as the key concepts of random forests, including ensemble methods and hyperparameter tuning.
The duration of the program is approximately 4 months, with learners completing a series of online courses and projects that culminate in a final capstone project.
The program is highly relevant to industries such as finance, healthcare, and marketing, where decision trees and random forests are widely used for predictive analytics and business intelligence.
Learners can expect to gain practical skills in programming languages such as Python and R, as well as experience with popular machine learning libraries and frameworks.
The Professional Certificate in Decision Trees and Random Forests in AI is a valuable addition to any data professional's toolkit, providing a solid foundation in supervised learning techniques and the ability to apply them to real-world problems.
Upon completion, learners can demonstrate their expertise to employers and clients, enhancing their career prospects and earning potential.
The program is also a great way to stay up-to-date with the latest developments in machine learning and AI, ensuring that learners remain competitive in the job market.

Why this course?

Decision Trees and Random Forests are crucial components in Artificial Intelligence (AI) that enable machines to make informed decisions based on data analysis. In the UK, the demand for professionals skilled in these areas is on the rise, with a projected growth rate of 14% by 2028 (Source: Employment Projections 2018 to 2028).
Year Number of Professionals
2020 10,300
2025 12,100
2030 14,800

Who should enrol in Professional Certificate in Decision Trees and Random Forests in AI?

Decision Trees and Random Forests in AI Ideal Audience
Data analysts and scientists with a basic understanding of machine learning concepts Individuals who want to improve their skills in predictive modeling and classification tasks, such as those working in finance, healthcare, or marketing in the UK, where 71% of businesses use machine learning to drive growth (Source: PwC).
Professionals with experience in programming languages like Python, R, or SQL Those who have a strong foundation in statistics and mathematics, and are looking to expand their toolkit with techniques like ensemble methods and feature engineering, with 60% of UK businesses using machine learning to improve customer experience (Source: Gartner).
Business professionals interested in using AI for decision-making Executives and managers who want to leverage AI-driven insights to inform strategic decisions, such as those in the UK's finance sector, where 55% of companies use machine learning to optimize operations (Source: Deloitte).