Professional Certificate of Competency in Practical Machine Learning Using Python for Engineers & Technicians (Online Learning)

Course Description

Overview

This professional development course is designed for engineers and technicians who need to harness machine learning technologies in their engineering work or become better problem solvers through the application of machine learning. This course will teach you to use Python Programming to work with machine learning applications and to apply supervised and unsupervised machine learning to engineering problems.

Learners are able to:
• Introducing fundamental programming concepts as it reduces the complexity of problem-solving by hiding the intricate arcane detail ‘under the hood.’
• Allows learners to leave the program with a strong capability in programming with Python, rather than superficially skimming through the language.
• Growing need for Python programming skills by industry (typically manufacturing, mining,
healthcare, and energy)

Accounting and Finance
COURSE CODE: CPM3144
DURATION: 3 months
START DATE: TBA
COURSE FEE: £973
AWARDING BODY: EIT’s Professional Certificate of Competency
  • Entry Requirements
  • Must be over 18 years at the time of application and who have previously achieved a level 3 qualification. There are no specific entry requirements for this qualification, but as a learner you will be ideally to be working with an organisation or role where they can demonstrate skills and apply knowledge. Alternatively, you could draw on previous experience within an organisation or use an organisation you are familiar with.

    The Qualifications have been designed to be accessible without artificial barriers that restrict access and progression:
      • IELTS minimum 5.0- 6.5 overall with no fail.
      • Pass 5 GCSE subjects or equivelant
    We consider applicants:

    Who have demonstrated some ability and possess Qualifications at Level 3, for example ‘A’ Levels or vocational awards.

      • Who have spent some time in an organisational role and wish to develop their careers further.
      • With professional experience looking to change careers through work-based learning.
  • Units & Assessment
  • Module Structure
    • Basic Machine Learning Terminology
    • Linear Algebra with Python using Numpy and Pandas
    • Probability Theory and Statistics with Python using Numpy and Pandas
    • Feature Engineering
    • Unsupervised Learning
    • Supervised Learning

  • Career Development
  • This course gives you the opportunity to start developing your career with dedicated career development support in addition to your online tuition. 

  • Progression
    • On completion of your studies, you may be given a full-time graduate opportunity by your employer
    • You may wish to further your studies by taking on an academic Master programme or a level 7 professional qualification

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