Data Analyst

Course details

Level

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Level 4

Duration

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15 months

Skills Coach support

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Every 4 weeks

You will achieve

Level 4 Data Analyst
BCS

Common job roles

  • Data Analyst
  • Data Manager 
  • Data Scientist 

Roles you may progress into

  • Digital Marketing Manager
  • Product Manager
  • Business Analyst
  • Data Engineer

Delivery of programme

Phase one

Induction

Your induction takes place within the first 2 weeks of starting your apprenticeship and is delivered by your Skills Coach during your first face-to-face coaching session.

Inductions include an informative presentation to discuss an overview of the programme and cover support that is available to you, details of our policies, and will introduce you to our systems and the resources available to you throughout your programme. You will undergo a Vocational Skills Scan (VSS) to identify your current skill set and where the apprenticeship can bring you most value.

Functional skills

We use BKSB tests to determine your current level of knowledge, to assess if you need further support with English and/or Maths.

If you do, our Functional Skills Training team will work with you to supply these skills. You will be supported through remote training sessions and workshops, which run for 3 days (for each). Once you feel comfortable, you can sit the Level 2 Maths and/or English exams. These qualifications are equivalent to an A* – C (4-9) grade at GCSE, they are fully certified by City & Guilds and can be used to further enhance your CV and skillset.

Phase two

Modules

Training centre learning: 

3 days 

What you will learn: 

  • Introduction to Data Analysis:
    • Types of Data
    • The Data Life Cycle
    • Structured and unstructured Data
    • Requirements for data analysis
    • Introduction to Big Data
  • Power BI (part one)
    • Loading, transforming, visualising data
    • Using Power Query Editor in Power BI

Training centre learning: 

3 days 

What you will learn: 

  • Data Fundamentals
    • Data security
    • Compliance & Audit Considerations
    • Data Architecture
    • Data Structures
    • Database design, implementing and maintenance
  • SQL Essentials
    • Creating DBs and tables
    • Interrogating DBs – Select
    • Using Joins

Training centre learning: 

3 days 

Remote training:

1 online supportive session

What you will learn: 

  • Good quality data
  • DA process life cycle
  • Data Analysis tasks
  • Domain context for DA

Training centre learning: 

2 days 

Exam: 

Your exam will take place on the second day in the afternoon.

Training centre learning: 

days 

Remote learning:  

1 online supportive session

What you will learn: 

  • R Fundamental Introduction
    • Data Structures in R
    • Basic stats in R
  • Exploratory Data Analysis
    • Visualisation tools
  • Hypothesis Testing
    • The Null and Alternative Hypothesis
    • Sampling and non-sampling error
    • Student’s T-test
    • Welch’s T-test
    • Wilcoxon Rank-Sum test
    • ANOVA

Training centre learning: 

3 days 

Remote learning:  

1 online supportive session

What you will learn: 

  • Modelling data
  • Quick measures in PBI
  • Building your own measures
  • R scripts in PBI
  • Mini projects

Training centre learning: 

3 days 

Remote learning:

1 online supportive session

What you will learn: 

  • Analytics in R
    • Validating analytical models: Within-Sum of Squares
  • Introduction to Machine Learning
    • Unsupervised methods such as;
      • K means clustering
      • Association rules

Training centre learning: 

3 days 

Remote training:

1 online supportive session

What you will learn: 

  • Predictive Analytics (part one – regression)
    • Supervised methods such as;
      • Linear regression
      • Logistic regression
  • Text Analysis
    • Handling text: Tagging, Stemming, Lemmatization
    • Regular expressions basics
    • Topic modelling
    • Measuring TFIDIF
    • Working examples in R – Word clouds

Training centre learning: 

3 days

Remote training:

1 online supportive session

What you will learn: 

  • Predictive Analytics (part two – classifiers)
    • Supervised methods such as;
      • Decision trees
      • Naive Bayes Classifier
  • Time series analysis
    • Time series decomposition
    • The Box-Jenkins method
    • Autocorrelation and partial autocorrelation functions
    • Covariance
    • ARMA and ARIMA models

Training centre learning: 

3 days 

Remote learning:  

1 online supportive session

What you will learn: 

  • Analytics for Unstructured Data – MapReduce and Hadoop
  • The Hadoop Ecosystem
  • In-database Analytics:
  • Advanced SQL and MADlib for In-database Analytics

Training centre learning: 

3 days 

Remote learning:  

Optional online support sessions 

What you will learn: 

  • Operationalising a data analysis project  
  • Creating the final deliverables
  • Data Visualisation techniques
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Your skills coach

You will have a skills coach assigned to support you throughout your apprenticeship, who will regularly arrange meetings with you both face-to-face and remotely.

During visits to your workplace, a variety of activities take place such as Tri-Party review meetings between you, your employer representative and your skills coach to discuss progress and set SMART targets. The skills coach will also work with your employer to complete your Employer Reference, a document which highlights key behaviours you have demonstrated.

portfolio

Your portfolio

Throughout the apprenticeship, you will contribute evidence towards your online e-portfolio. We use e-portfolios as they are accessible from anywhere, and enable you to track your progress throughout your apprenticeship.

You’ll have access to your personal dashboard, which shows you a number of key milestones and deadlines coming up, such as the training you have completed, work that is due, and any gaps in your portfolio of evidence.

Your skills coach will be available to contact at any point throughout the apprenticeship and will advise you how to provide the best evidence.

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Off-the-job training

Off-the-job (OTJ) training is comprised of, but not limited to activities such as: training with Estio, shadowing, journal entries and projects for e-portfolio. Completed within working hours as agreed with the employer but average at 6 hours per week (20% of your time on your apprenticeship).

You can track your OTJ progress on your e-portfolio.

Phase three

Assessment Gateway, preparation & administration week

The Gateway week is used to finetune your skills and offer a simulated Synoptic Project for systems familiarisation, and to ensure that your Summative Portfolio and Employer Reference are completed before entering into EPA.

Phase four

End Point Assessment

Learners are assessed by an End Point Assessment Organisation, chosen by the Employer. Included in EPA is Evidence Submission (portfolio & certificates), Employer Reference, Synoptic Project and an Interview.
The Independent Assessor will feedback the results (Pass, Merit or Distinction) and the ESFA will provide your certificate.

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Where can this apprenticeship take me?

The Level 4 Data Analyst apprenticeship will give you the skills and experience to work effectively in roles such as Data Analyst, Data Manager, Data Scientist, Data Modeller, Data Architect, or Data Engineer.

After achieving a recommended minimum of 1 years experience within your role after completion (this is subject to employers) you can begin a Level 6 Data Scientist apprenticeship.

Level 6 Data Scientist roles

Data Scientist, Informatics, Data Engineer

More information about this apprenticeship can be found on the institute for apprenticeships website.

University study

Level 4 apprenticeships are the equivalent to a foundation degree. If you wish to study further whilst staying in work, some univeristies will offer the ability to learn remotely. If you wish to take a break from work, you may need to apply for a student loan whilst you study.

Current vacancies

Get in touch!

Call our team on 01133 500 333 or fill out our enquiry form below