inspire Technical Training

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Our advanced technology training programs are tailored for each of our clients to ensure the level of progression is suited to the employees.  

Flexible training programs offering remote capability and custom schedules giving a perfect fit for training junior employees or re-skilling current employees within in-demand technologies.

A seamless learning experience, with a full hosted course on our Learning Management System, delivered by a full-time instructor (SME) with a training assistant for each class.  

Our team provides all administrative support and weekly feedback reports on the employee performance and wellbeing.

Our Data Professional training course covers a host of important data skills, Python, SQL, Azure Databricks & Power BI. 

• Data Fundamentals
• ETL
• Data Analysis
• Data visualization
• Advanced Python
• Data Science - ML & AI

This course covers the tools, concepts, and techniques for becoming a data professional focusing on artificial intelligence (AI) and Machine Learning (ML) technologies.  

Training with technical skills modules such as:

• Introduction to Artificial Intelligence
• Programming Fundamentals
• Mathematics for AI
• Machine Learning Basics
• Deep Learning Foundations
• Natural Language Processing (NLP)
• Computer Vision
• Reinforcement Learning
• AI Ethics and Responsible AI

Combining this our specific modules provides the skills required for the team and individual projects to complete the course.

Our cloud training is across the major providers, AWS, GCP and Azure.  From foundational training for graduates through to re-skilling AWS employees to GCP to ensure your workforce has multi cloud capability.  Our modules include:

• Introduction to Amazon Web Services (AWS) AWS Pricing & Cost Management
• Introduction to Elastic Compute Cloud (EC2)
• Introduction to Simple Storage Service (S3)
• Introduction to Serverless Cloud Computing
• Introduction to Management & Governance
• Overview of Storage, Database, & Data Migration

The ITSM course build upon the foundation guidance from ITIL relating to 3 key operational processes to provide greater insight regarding methods and technique, organizational considerations, and cultural challenges:

• The Problem Management Practice
• The Incident Management Practice focused on Major Incident Management
• The Continual Improvement Practice

Also delivering pre-exam revision day will provide employees with an opportunity to explore any of the ITIL 4 Foundation content that they require additional guidance and insight to better prepare for their formal exam.

Our teaching methods will include an introductory face-to-face workshop, online lectures, interactive coding sessions, online quizzes, small group work and project-based learning. 

Teaching will be delivered online via video, and learning content and interactive elements will be delivered via our learning management system (LMS) with full support from our industry leading professors. 

The aim is to equip you with the knowledge and skills necessary to apply machine learning techniques to solve real-world problems effectively. 

To develop your ability to navigate and solve complex data-driven problems using sophisticated ML techniques and prepare for your career confidently and responsibly using ML tools.

To ensure you are able to fully benefit from the course, we will ask you to complete an online python assessment. 

You should have competent skills in Python, familiarity with common Libraries such as NumPy, Matplotlib, Pandas etc.

You will also need competency in Maths and Statistics.

This program is designed to provide you with a deep and practical understanding of machine learning (ML) using Python, one of the most popular programming languages in data science.

Our training modules cover the below topics:

• What is Machine Learning?
• Supervised Learning: Classification
• Supervised Learning: Regression
• Unsupervised & Reinforcement Learning
• Common Challenges
• Effective Training Techniques
• Pipeline For Machine Learning Projects
• Advanced ML Topics

By the end of the course, it is expected that you will be able to:

• Explain foundational ML concepts and their practical implications.
• Apply various ML techniques to analyse and interpret data.
• Design and evaluate ML models to address specific challenges.
• Implement effective strategies to improve model accuracy and efficiency.
• Conduct comprehensive ML projects from data collection to model deployment.

Over 50 hours of scheduled (live) teaching and learning activities will be delivered online, with the remaining hours for scheduled study and practical classes / workshops over a 5-week period with support staff. 

There is no formal assessment for this module, however you will be expected to complete several practical assignments and online quizzes during the course for which you will receive formative feedback.  

These will inform and indicate your level of progress in relation to the module learning outcomes.