Data Analyst (Level 4)

Apprenticeship Standard Data Analyst (Level 4)

Phase 1Induction & Initial Assessment

Phase 2Training modules and contact from Skills Development Coach

1 2 3 4 5 6 7 8 9 10 11

Phase 3Assessment Gateway

Phase 4End Point Assessment

Training Centre & Remote

Phase 1 Induction & Initial Assessment Skills Coach visit

Phase 2 1. Introduction to Data Analysis 3 days 3 online supportive sessions

2. Data Fundamentals with SQL 2 days 3 online supportive sessions

3. Data Fundamentals in R 3 days 3 online supportive sessions

4. Power BI Basics 2 days 3 online supportive sessions

5. R Fundamentals and statistics 3 days 3 online supportive sessions

6. Statistical methods and Exploratory Data Analysis 3 days 3 online supportive sessions

7. Analytics in R and intro to Machine Learning 3 days 3 online supportive sessions

8. Predictive Analytics 1 and Text Analysis 3 days 3 online supportive sessions

9. Predictive Analytics 2 4 days 3 online supportive sessions

10. Big Data Fundamentals, SQL, MADLib and Cloud Infrastructure 3 days 3 online supportive sessions

11. Exam Workshop 3 days Optional online support sessions

Phase 3 Assessment Gateway Up to 1 week* Training Centre only

Phase 4 End Point Assessment 3 - 5 days Training Centre only

Delivery breakdown

*To be arranged by your Skills Development Coach

Course DetailsInduction/Initial Assessment

Skills Development Coach will conduct the induction in their first visit

Functional Skills

If required, learners will sit a Maths and/or 3 English exams.Workshops can take up to 3 days.Each exam takes up to 2 hours.

Data Fundamentals in R

• Requirements for Data Analysis• Data Analysis Tasks• Domain Context for Data

Analytics

R Fundamentals and Statistics

• Intro to R Studio• Base R• R objects in details;

including atomic vectors, Attributes, Matrices, Lists, Arrays and Data Frames.

• R Packages essentials• Statistics in R

Statistical methods and Exploratory Data Analysis

• Hypothesis development/testing, Visualisation, EDA and Data prep

• Statistical methods• Tidyverse Packages

Analytics in R and intro to Machine Learning

• Introduction to Machine Learning Concepts and Use Cases.

• Unsupervised learning:- K-means Clustering- Association Rules.

Introduction to Data Analysis

• Overview to the Data Ecosystem• Introduction to Big Data and

driving factors 4 V’s• IRIS Analytical Lab in Excel• Data Driven Culture• Types of Data• The Data Life Cycle• Structured and

unstructured Data

Data Fundamentals with SQL

• Database Design, Implementation and maintenance

• Data Structures• Data Architecture • Compliance & Audit

Considerations

Power BI Basics

• Intro to Power BI & Orientation. • Using Query Editor in Power BI and

connecting to Excel.• Editing and Publishing Reports.• Quality Issues for Data

Analysis.• Take the BCS KM2 exam

Predictive Analytics 1 and Text Analysis

• Linear and Logistic regression• Text Analysis and Sentiment

Analysis with R.

Predictive Analytics 2

• Exploring & Visualizing Times Series

• Benchmark Methods & Forecast Accuracy

• Decision trees• Naïve Bayes

Big Data Fundamentals, SQL, MADLib and Cloud Infrastructure

• SQL OLAP extensions, Windows functions, user defined functions, and aggregates

• Explore Apache MADlib for in-SQL Machine Learning.

• Big Data use case analysis. • Hadoop Ecosystem Overview. • Interface exploration• Big Data on Azure Analysis

done in Pig and Hive.• Prepare for exam

BCS Exam workshop

• Operationalising a data analysis project

• Exam prep (Past papers, topic questions, topic reviews).

• Exam on final day (if ready). Otherwise arrange a date no later than 2 weeks

Assessment Gateway, Assessment Preparation & Administration Week

(Up to 1 week in the training centre)Preparation week to understand the four elements of the gateway.

Assessment Phase

• Summative Portfolio• Synoptic Project• Technical Interview with SME• Employer Reference

Achievement of Apprenticeship

BCSData Analyst(Level 4)

www.estio.co.uk 01133 500 333