Higher Technical Qualification (HTQ) - NCFE Diploma Level 4: Data Analyst
Key Facts
Duration: 7-8 months
Start Dates:
COHORT 4 - Mondays - Starts Monday 27th January 2025
COHORT 5 - Thursdays - Starts Thursday 20th February 2025
COHORT 6 - Saturdays - Starts Saturday 15th March 2025
COHORT 7 - Fridays - Starts Friday 28th March 2025
Study Modes: Fully remote, live training sessions, self study assessments
Entry requirements: Learners must be aged 18 or over.
Learners must own (or have access to) a laptop or desktop computer with internet access. A Windows device is preferred to access the specialist data software we will use and your computer will need the ability to download free software.
Cost: Introductory price £500* ends January 2025! (Full price £1400)
Who is this for: The HTQ Level 4 Diploma in Data Analytics is perfect for:
Career Starters entering data analytics.
Career Changers transitioning to data-focused roles.
Current Employees who use data in their roles to inform decisions. This could include Marketing, Sales, Finance, IT, MI or Administration.
Employers training staff to leverage data insights.
Flexible and hands-on, it’s designed for learners at all stages.
*T&C's apply
Course Overview
Our Data Analyst Higher Technical Qualification (HTQ) is designed to launch your career in data science, whether you are new to the field or considering a career shift. You will acquire programming skills and experience using a range of industry-standard software, and develop abilities in data interpretation, statistical analysis, and solving problems based on data.
This qualification will also help you become a skilled communicator, adept at presenting concepts and ideas tailored to various audiences. Additionally, you will obtain valuable transferable skills such as research, evaluation, and teamwork.
This Level 4 Diploma Data Analyst qualification is broken down into 6 units:
Data fundamentals and lifecycle
Data mining and statistical analysis
Data structure and databases
Organisation data
Legislation and security standards applied to data analytics
Stakeholder engagement and user experience in data analytics
As an NCFE-approved centre, Fareport Training is now positioned to deliver this cutting-edge programme, designed to equip learners with the skills and knowledge necessary to thrive in the rapidly evolving field of data analysis.
The HTQ Level 4 Diploma in Data Analysis will provide students with a comprehensive understanding of data collection, processing, and interpretation, preparing them for a variety of roles within the tech and data-driven sectors.
This course will run for 6 months teaching time - 1 day a month with self study work in between each lesson. The lessons will be via Microsoft Teams and will be live with our expert trainers, each session will be recorded for reference purposes.
An introduction to NCFE Higher Technical Qualifications with David Rowley, HTQ product manager, NCFE
Course Dates
We have three cohorts starting this year, they each have an induction and 6 1 day monthly teaching sessions. To apply please complete the contact form.
|
Module |
Cohort 4 Mondays |
Cohort 5 Thursdays |
Cohort 6 Saturdays |
Cohort 7 Fridays |
|---|---|---|---|---|
|
Data Fundamentals and Lifecycle |
Monday 27th January |
Thursday 20th February |
Saturday 15th March |
Friday 28th March |
|
Data Mining and Statistical Analysis |
Monday 17th February |
Thursday 20th March |
Saturday 12th April |
Friday 25th April |
|
Data Structure and Databases |
Monday 17th March |
Thursday 1st May |
Saturday 24th May |
Friday 23rd May |
|
Organisational Data |
Monday 14th April |
Thursday 29th May |
Saturday 28th June |
Friday 20th June |
|
Legislation and Security Standards applied to Data Analysis |
Monday 12th May |
Thursday 26th June |
Saturday 26th July |
Friday 18th july |
|
Stakeholder Engagement and User Experiences in Data Analytics |
Monday 16th June |
Thursday 24th July |
Saturday 16th August |
Friday 22nd August |
Course details - Modules 1-6
Here is an outline of the 6 modules for the Data Analytics HTQ. For each module it details an overview of what is included and technical requirements.
|
Module |
Technical Requirements |
|---|---|
|
Data fundamentals and lifecycle - Credits: 30 This module equips learners with the skills to extract meaningful insights from complex datasets using advanced statistical methodologies. It covers key statistical techniques such as descriptive statistics, hypothesis testing, and correlation analysis. Learners explore data mining and predictive analytics to identify patterns and trends, applying statistical tools like Python and SQL. This unit focuses on how to use these methods to support informed decision-making in data-driven environments. |
OneFile Microsoft Teams Microsoft Excel Google Sheets |
|
Data Mining and Statiscal Analysis: Credits 30 This module equips learners with the skills to extract meaningful insights from complex datasetsusing advanced statistical methodologies. It covers key statistical techniques such as descriptivestatistics, hypothesis testing, and correlation analysis. Learners explore data mining and predictiveanalytics to identify patterns and trends, applying statistical tools like Python and SQL. This unit focuses on how to use these methods to support informed decision-making in data-driven environments. |
OneFile Microsoft Teams Microsoft Excel Google Sheets Microsoft Power BI desktop Jupyter Notebook |
|
Data Structure and Databases - Credits: 20 This module introduces learners to fundamental concepts of data organisation and storage. It covers key data structures such as arrays, lists, and trees, as well as database management systems. Learners will explore relational databases, SQL, and how to design, create, and query databases effectively. The unit emphasises how proper data structuring enhances efficiency and accessibility in managing large datasets, preparing learners to handle data in real-world applications. |
OneFile Microsoft Teams Microsoft Excel Google Sheets Google BigQuery |
|
Organisational Data - Credits: 20 This module equips learners with the skills to extract meaningful insights from complex datasets using advanced statistical methodologies. It covers key statistical techniques such as descriptive statistics, hypothesis testing, and correlation analysis. Learners explore data mining and predictive analytics to identify patterns and trends, applying statistical tools like Python and SQL. This unit focuses on how to use these methods to support informed decision-making in data-driven environments. |
OneFile Microsoft Teams Microsoft Excel Google Sheets Powerpoint Google slides |
|
Legislation and Security Standards applied to Data Analytics - Credits: 10 This module provides learners with an understanding of the legal and ethical frameworks surrounding data usage. It covers key legislation such as the General Data Protection Regulation (GDPR) and other data protection laws, as well as industry-specific security standards. Learners explore best practices for ensuring data privacy, confidentiality, and security in data analytics, focusing on compliance and risk management in handling sensitive information. |
OneFile Microsoft Teams Microsoft Excel Google Sheets PowerPoint Google slides |
|
Stakeholder Engagement and User Experience in Data Analytics - Credits: 20 This module teaches learners how to effectively communicate and collaborate with stakeholders throughout the data analytics process. It covers techniques for identifying stakeholder needs, translating data insights into actionable recommendations, and ensuring that data-driven decisions align with business objectives. Additionally, the unit focuses on improving user experience by delivering clear, relevant, and user-friendly data presentations and solutions that meet stakeholder expectations. |
OneFile Microsoft Teams Microsoft Excel Google Sheets PowerPoint Google slides |
Why choose to learn with Fareport Training
Fareport Training was established in 1981 in order to offer young people a route into work through work based training. In 2014 the business was purchased with support from entrepreneur Theo Paphitis by Natalie Cahill and Marinos Paphitis. Since then we have been building on Fareport's excellent reputation for high quality training and delivering training and apprenticeships across England. We are proud to offer:
Expert-Led Instruction: Gain insights from industry leaders and seasoned professionals.
Cutting-Edge Curriculum: Stay ahead with the latest trends, tools, and techniques.
Flexible Learning Options: Balance your education with your professional and personal life.
We work with trusted brands such as...
How do I apply?
Simply complete the Register Your Interest form at the bottom of this page and you will be sent the course brochure. For more information and support with your enquiry please contact Fareport by emailing DataHTQ@fareport.co.uk or calling 01329 825805.
Frequently Asked Questions
Higher Technical Qualifications (HTQ) are Level 4 and 5 qualifications that bridge the gap between A/T Levels and degree programs. Developed collaboratively with awarding bodies, employers, and businesses, these qualifications are tailored to provide learners with the targeted training, knowledge, and skills required for their career paths. HTQs are intended to be pursued as standalone qualifications, offering an alternative to apprenticeships, rather than being part of an apprenticeship scheme.
Learners must be aged 18 or over.
Learners must own (or have access to) a laptop or desktop computer with internet access. A Windows device is preferred to access the specialist data software we will use and your computer will need the ability to download free software.
We are offering an introductory price of £500 until the end of January 2025 after that the will increase to £1400 - which is still very competitive. We offer private payment terms and also Student Loans (from February 2025), to discuss payment options please register your interest.
The structure will be taught sessions every month which trainers will deliver online. This will consist of teaching the knowledge and skills of the learning outcomes of each of the modules. There will be interactive tasks, discussions, and activities throughout the sessions.
The modules require assessments to demonstrate the knowledge and skills of the areas, and this will be communicated and explained in the teaching sessions so allows the learners to ask questions and make notes.
The assessments will need to be completed through self-study in between the monthly teaching sessions.
The teaching resources have been designed to have clear slides of the knowledge taught and they will be available for you to use these when completing your assessments in your self-study time.
Everything you need for the course you will have. You will be expected to complete some extra resources or tasks if you would like to aim for a high grade. The grading system is a pass, merit or distinction. All of this will of course be given to you in the induction / sessions.
We aim to give all the knowledge and skills throughout the teaching sessions and complete practical activities which will support the knowledge you are learning. We can support all learners throughout the course however, if any learners need additional support trainers will be able to set up individual meeting to support. Questions and answer sessions, drop-in sessions will also be available to support learners.
Once you have started the course and attended the induction session. Here, you will meet your trainer and be given all contact details and confirm course dates again. You will have e-email access to your trainer and all course materials will be uploaded to our e-portfolio system which is ONEFILE.
You will be shown how to use ONEFILE in the sessions to collect course materials (Once you have completed the module teaching session) and then shown how to upload your completed work and collect feedback.
Apply today!
Please send us your details and our HTQ Enrolment team will be in touch to answer any questions and tell you the next steps.
