QUALIFI
Level 3
QN: 610/5600/5
Curriculum Active
Qualifi Level 3 Extended Diploma in IT and Data Science
Official qualification regulated by Ofqual, awarded by QUALIFI. Classified as a Vocationally-Related Qualification. Total guided learning hours: 1145 hours.
Qualification Level
Level 3
Awarding Body
QUALIFI
Syllabus Units
26 Units
Guided Hours
1145 hrs
Instant access to interactive lessons, quizzes, and spaced revision.
Course Syllabus & Study Modules
Complete breakdown of verified curriculum topics and learning objectives.
1
An Introduction to Marketing
Verified
Key Learning Objectives:
- Know the importance of marketing in an organisation.
- Understand marketing research and planning.
- Understand how and why customer groups are targeted
- Be able to develop a coherent marketing mix.
2
An Introduction to the Business Environment
Verified
Key Learning Objectives:
- Know different types of Businesses and their ownership and the different types of stakeholders.
- Understand how businesses are organised
- Understand how Businesses achieve their target purpose
- Identify legal, political, and social factors that can affect businesses.
3
Business Resources
Verified
Key Learning Objectives:
- Know how human resources are managed.
- Understand the purpose of managing physical and technological resources
- Identify ways to access different sources of finance
- Understand financial statements.
4
Coding and Website Development
Verified
Key Learning Objectives:
- Understand the purpose and types of coding.
- Understand web architecture and components.
- Be able to create interactive websites.
5
Communication and Cultural Skills for Higher Education
Verified
Key Learning Objectives:
- Communicate fluently, accurately and effectively, speaking on a range of topics, with appropriate control of grammar, vocabulary and register.
- Understand different learning styles.
- Understand the concept of culture, cultural values and how different cultures can be defined
- Understand academic culture and conventions
6
Computer Systems
Verified
Key Learning Objectives:
- Understand the purpose of computer systems.
- Understand computer system components.
- Be able to configure computer systems.
7
Creating and Interpreting Visualisations in Data Science
Verified
Key Learning Objectives:
- Understand the role and importance of visualizing data.
- Understand basic plots and charts.
- Be able to create and interpret plots and charts.
8
Cyber Security
Verified
Key Learning Objectives:
- Understand cyber security.
- Understand core terminology and key aspects of cyber security.
- Understand cyber threat intelligence.
9
Data Analytics with Python
Verified
Key Learning Objectives:
- Be able to load and save data
- Be able to perform basic data wrangling and exploratory analysis.
- Be able to perform basic data cleaning tasks.
- Be able to perform basic data transformation tasks.
10
Data and Descriptive Statistics in Data Science
Verified
Key Learning Objectives:
- Understand the different types of data and their characteristics.
- Understand measures of centre.
- Understand measures of spread.
- Understand measures of symmetry and peakness.
- Understand measures of joint variability and linear relation.
11
Decision Trees in Data Science
Verified
Key Learning Objectives:
- Understand what a decision tree is in data science.
- Understand how to construct a decision tree in data science.
- Be able to perform calculations using decision tree metrics in data science.
- Be able to build a decision tree model in data science.
12
English for Higher Education
Verified
Key Learning Objectives:
- Be able to utilise different ‘pre’, ‘while’ and post reading strategies to understand academic texts.
- Be able to demonstrate an appropriate academic vocabulary.
- Be able to structure sentences, paragraphs and full texts to suit academic requirements.
- Be able to utilise ‘pre’, ‘while’ and post listening strategies to understand different speakers and academic topic information.
13
Fundamentals of Data Analytics
Verified
Key Learning Objectives:
- Understand the processes and types of data analytics.
- Understand the data analytics ecosystem.
- Understand the issues and methods for dealing with data quality issues.
- Understand the issues and methods of basic data transformations.
14
Graphs and Graph Data Science
Verified
Key Learning Objectives:
- Understand different types of graphs and their properties.
- Understand the core types of graph data models.
- Understand the graph ecosystem.
- Understand the types of graph data science and graph algorithms.
15
Human Resource Management
Verified
Key Learning Objectives:
- Know the internal and external factors involved in human resources planning in organisation.
- Understand know how an organisation motivates its employees.
- Know how organisations manage and measure employee performance.
- Understand how organisations co
- operate with their employees.
16
K-means Clustering in Data Science
Verified
Key Learning Objectives:
- Understand the theory of k-means clustering.
- Understand how to evaluate k-means clusters
- Be able to create and evaluate a k-means model.
17
Linear Regression in Data Science
Verified
Key Learning Objectives:
- Understand the basic theory of linear regression.
- Understand regression metrics and how to evaluate a regression model.
- Be able to perform regression calculations and analysis.
- Be able to create linear regression models.
18
Logistic Regression in Data Science
Verified
Key Learning Objectives:
- Understand the basic theory of logistic regression.
- Be able to perform logistic regression calculations.
- Be able to create logistic regression models.
19
Machine Learning Methods and Models in Data Science
Verified
Key Learning Objectives:
- Understand the concepts of basic supervised machine learning models
- Understand the concepts of basic unsupervised machine learning models
- Understand the concepts of basic reinforcement learning.
20
Mobile Communications
Verified
Key Learning Objectives:
- Understand the uses and features of mobile communication devices.
- Understand the communication technologies used in mobile devices.
- Understand the implications of mobile communications technology.
21
Networks
Verified
Key Learning Objectives:
- Understand networking principles.
- Understand how net
- work hardware and software components are connected.
- Understand the usage and security concerns relating to networking.
22
Python for Data Science
Verified
Key Learning Objectives:
- Understand the design philosophy and features of Python.
- Understand Python’s basic data types.
- Be able to create and manipulate lists and tuples.
- Be able to create and manipulate sets and dictionaries.
- Be able to write Python functions and flow statements.
23
Social Media for Business
Verified
Key Learning Objectives:
- Understand the importance of using social media in a business environment.
- Understand the need for social media content planning and publishing in a business environment.
- Be able to develop a policy and a plan to use social media in a business environment.
24
Synthetic Data for Privacy and Security in Data Science
Verified
Key Learning Objectives:
- Understand the core issues of data privacy and security.
- Understand the basics of differential privacy.
- Understand the core issues of synthetic data.
- Understand the synthetic data ecosystem.
- Be able to create anonymised or fake data.
25
The Field of Data Science
Verified
Key Learning Objectives:
- Understand the core issues of data science.
- Understand the core issues of data and big data.
- Understand the core issues of artificial intelligence.
- Understand the core issues of machine learning.
- Understand the core issues of deep learning.
26
The Machine Learning Process
Verified
Key Learning Objectives:
- Understand the machine learning process.
- Understand the data preparation process for machine learning models.
- Understand how to evaluate machine learning models.
- Be able to evaluate classification models.
- Understand the issues of bias and variance in models.
Regulatory & Verification Details
- Qualification Number (QN)
- 610/5600/5
- Regulated Status
- Available to learners
- Awarding Body
- QUALIFI
- Qualification Type
- Vocationally-Related Qualification
- Operational Start
- Apr 2025