About Course

πŸ€– Short Online Diploma in Machine Learning

(Internationally Accredited | 45 CPD Points | 3-Month Program)

Step into the future of technology with our Short Online Diploma in Machine Learningβ€”a globally recognized program designed to equip learners with the essential tools, algorithms, and skills needed to master intelligent systems and predictive modeling.

This course is accredited internationally by CA Worldwide (UK) and the CPD Index, and offers 45 CPD Points, making it a powerful addition to your professional development and career advancement toolkit. With 45 hours of immersive content, this flexible, 100% online course can be completed in approximately 3 months, at your own pace.


πŸ“š Course Overview

Machine Learning (ML) is transforming industriesβ€”from healthcare and finance to marketing and transportation. This course provides a hands-on, beginner-friendly introduction to the field, while covering advanced machine learning models, algorithms, and real-world applications.

You’ll learn how machines learn from data, how to train predictive models, and how to deploy intelligent systems that can adapt, classify, and forecast outcomes.


βœ… What You Will Learn

  • Core concepts and types of Machine Learning (Supervised, Unsupervised, Reinforcement)

  • Understanding data: cleaning, preparation, feature engineering

  • Training algorithms such as Linear Regression, Decision Trees, KNN, SVM, NaΓ―ve Bayes, and Random Forests

  • Introduction to Neural Networks and Deep Learning

  • Evaluating model performance: accuracy, precision, recall, ROC-AUC

  • Handling overfitting and underfitting with regularization techniques

  • Real-world case studies: classification, prediction, recommendation

  • Using Python and Scikit-learn for end-to-end model development

  • Introduction to tools like Jupyter Notebooks, TensorFlow, and Google Colab

  • Interpreting ML outputs for business insights and deployment readiness


πŸ• Course Duration & Structure

  • Total Duration: 45 Hours

  • Suggested Timeline: Complete in 3 Months

  • Mode: Fully Online & Self-Paced

  • Access: Lifetime access to all learning materials and updates

  • Final Certification: Upon successful completion of the course project or final assessment


πŸ… Accreditation & Recognition

This diploma is awarded by institutions of global repute and carries significant professional value:

  • Accredited by CA Worldwide (UK Accreditation Authority)

  • Listed under CPD Index (UK)

  • Earns 45 CPD Points, meeting international CPD standards

A highly credible certification that adds weight to your resume, enhances your professional standing, and is recognized by employers and institutions worldwide.


πŸ‘¨β€πŸ’» Who Should Enroll

  • Beginners interested in Artificial Intelligence and Machine Learning

  • Students in Engineering, Computer Science, Mathematics, or Business

  • Data enthusiasts and self-learners looking to build technical skills

  • Developers and software engineers aiming to specialize in ML

  • Analysts and decision-makers in need of automated insights

  • Professionals preparing for roles in AI, Data Science, or Robotics

  • Anyone curious about machine intelligence and future technologies


πŸš€ Career Opportunities

Upon completion, learners can confidently apply for roles such as:

  • Machine Learning Engineer (Entry-Level)

  • Data Scientist

  • AI/ML Research Assistant

  • Predictive Analytics Specialist

  • Software Developer with ML Focus

  • AI Consultant or Product Analyst


🌐 Why Choose This Diploma?

βœ” Accredited Globally – Trusted Certification
βœ” 45 CPD Points – Recognized Professional Development
βœ” Covers Theory + Hands-on Coding + Real-World Projects
βœ” Lifetime Access and Flexible Learning
βœ” Beginner-Friendly – No Prior Experience Needed
βœ” Taught with Practical Tools and Live Datasets


This is your opportunity to future-proof your career and gain a foothold in one of the most in-demand fields of the 21st century.

Enroll today and become a certified Machine Learning practitioner in just 3 months.

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What Will You Learn?

  • Understand the fundamentals of Machine Learning and its real-world applications
  • Differentiate between supervised, unsupervised, and reinforcement learning
  • Prepare and preprocess datasets for ML modeling
  • Perform feature selection and engineering to improve model performance
  • Implement key algorithms like Linear Regression, Logistic Regression, Decision Trees, SVM, KNN, and NaΓ―ve Bayes
  • Train and evaluate models using Python libraries such as Scikit-learn
  • Analyze model performance using metrics like accuracy, precision, recall, F1 score, and ROC-AUC
  • Apply regularization techniques to prevent overfitting
  • Explore introductory deep learning and neural networks
  • Use Jupyter Notebook and Google Colab for hands-on coding practice
  • Develop ML workflows for classification, prediction, and recommendation systems
  • Interpret ML outputs and translate them into business insights
  • Complete real-world case studies and hands-on projects
  • Gain practical experience with tools like TensorFlow and Pandas
  • Learn basic model deployment concepts for real-time usage

Requirements

  • No prior experience in machine learning required
  • Basic understanding of high school mathematics (algebra, probability) is helpful
  • Familiarity with Python is beneficial but not mandatory (introductory tutorials included)
  • Access to a laptop or desktop with stable internet connection
  • Use of recommended browsers like Chrome or Firefox for best experience
  • All tools and platforms used (e.g., Jupyter, Google Colab) are free and accessible online
  • Complete all modules, quizzes, and final project to earn the diploma
  • Self-paced learning – you can study anytime within the 3-month window
  • Lifetime access to course materials for revision and reference
  • Support available for technical and academic queries during the course

Audience

  • Aspiring machine learning engineers and AI professionals
  • Students in computer science, engineering, data science, mathematics, or related fields
  • Software developers and programmers looking to expand into machine learning
  • Data analysts and scientists aiming to deepen their ML skills
  • Professionals seeking a career transition into AI or emerging tech
  • Entrepreneurs and startup founders interested in leveraging intelligent systems
  • Researchers and academic professionals exploring applied machine learning
  • Business and tech consultants wanting to integrate ML into solutions
  • Tech enthusiasts curious about machine learning and predictive modeling
  • Job seekers aiming to enhance their resume with an accredited ML certification

Course Content

Live Lessons

  • Saturday Live Classes (2 Hours Sessions)
  • Sunday Live Classes (2 Hours Sessions)

Final Project

Student Query

Instructors

Scholastia (Training Provider)

Scholastia (Training Provider)

4.7
1497 Students
14 Courses

Feedback

4.0
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Review (1)

  1. Nitish Naruka

    Nitish Naruka

    3 months ago
    Really great course with plenty of practical projects.

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