Access to Higher Education Diploma (Data Science)

Modules

Unit 1: Academic Writing Skills

On completion of this unit, you will:

• Be able to write with relevance in responding to an academic task
• Know how to interpret and discuss ideas and issues in responding to a set, academic writing task
• Be able to summarise for academic purposes, selecting key points, information or central ideas

Unit 2: Preparing a Written Assignment

On completion of this unit, you will:

• Understand how to use key information sources
• Understand why sources are acknowledged and referenced
• Understand a range of reading strategies
• Understand note-making methods
• Understand how to plan, draft, and produce a written assignment

Unit 3: Using the Internet and Email

On completion of this unit, you will:

• Be able to use e-mail
• Be able to use the Internet for research and communication
• Understand how to evaluate Internet resources

Unit 4: Using Spreadsheet Software

On completion of this unit, you will:

• Be able to use spreadsheet software
• Be able to perform calculations on spreadsheet data
• Be able to use spreadsheet software to create and develop graphs and charts

Unit 5: Introduction to AI, Machine Learning and Deep Learning

On completion of this unit, you will:

• Understand the core issues of artificial intelligence
• Understand the core issues of machine learning
• Understand the core issues of deep learning

Unit 6: What is Data and Data Science?

On completion of this unit, you will:

• Understand the core issues of data science
• Understand the core issues of data and big data
• Understand the data science ecosystem

Unit 7: Creating and Interpreting Visualisations

On completion of this unit, you will:

• Understand the importance of visualising data
• Understand basic plots and charts
• Understand the features of Python Libraries
• Be able to create and interpret plots and charts

Unit 8: Foundations of Data Analytics

On completion of this unit, you will:

• Understand the key 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

Unit 9: Foundations of Machine Learning

On completion of this unit, you will:

• 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

Unit 10: Introduction to Python Part 1

On completion of this unit, you will:

• Understand the design philosophy and core features of Python
• Understand the Python ecosystem
• Understand Python’s basic data types

Unit 11: Introduction to Python Part 2

On completion of this unit, you will:

• Be able to create and manipulate lists
• Be able to create and manipulate tuples
• Be able to create and manipulate sets
• Be able to create and manipulate dictionaries
• Be able to write and use basic Python functions

Unit 12: Data Analytics with Python

On completion of this unit, you will:

• Be able to create and save data
• Be able to merge data sets
• Be able to perform basic data exploratory analysis
• Be able to perform basic data-cleaning tasks
• Be able to perform basic data transformation tasks

Unit 13: Machine Learning Methods and Models

On completion of this unit, you will:

• Understand the core concepts of basic supervised machine learning (ML) models
• Understand the core concepts of basic unsupervised machine learning models
• Understand the core concepts of reinforcement learning

Unit 14: Data and Descriptive Statistics

On completion of this unit, you will:

• 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

Unit 15: Machine Learning Topic

On completion of this unit, you will:

• Be able to plan a machine learning modelling project in Data Science

Be able to build a machine-learning model

Entry Requirements

You must hold Level 2 qualifications in both English and Maths or be working towards them alongside studying for your Access to Higher Education Diploma.

University Entry Criteria

It must be reiterated that each university will set its own admission criteria. So, you must check with your desired institution if your Access to HE Diploma and other qualifications will be accepted. In many cases, to get started at university you will need: - A certain number of credits passed with a merit or a distinction grade - A face-to-face interview at the university - Literacy and numeracy assessments provided by the university - Course-related work placements or work experience - GCSE Grade C/4 or above in Maths and English (or equivalent Level 2 such as Functional Skills/Key Skills, etc.) It is your responsibility to check that your Access to Higher Education Diploma will be accepted as part of these entry requirements for your chosen degree. learndirect will not be held accountable if completing this Access to Higher Education Diploma doesn’t secure you a position with a higher education institution.

Minimum age restriction

An Access to Higher Education Diplomas is designed to support students to progress to university who have substantial experience of life outside of formal education which they have gained since completing compulsory schooling.

Average completion timeframe

The average time it takes our learners to complete the course is 9-12 months.

Assessment requirements

A range of assessment methodologies are used, including:

• Academic report
• Essay
• Case study analysis
• Illustrated report
• Journal article
• Portfolio
• Academic poster
• Presentation (video and audio recording)
• Developing promotional activity
• Series of questions
• Academic writing skills tasks

Exams required

There are no exams included in the assessment of the course.

Is Membership Required?

No membership is required to enrol on this course.

Additional requirements

Learners must be actively studying for a minimum of six months before results can be ratified and certificates ordered. The six-month period does not start until you have passed unit 2 of your course and you must be submitting assignments regularly (in line with the deadlines in your Individual Learning Plan) to meet this six-month requirement. Certificates can only be issued once your course is paid for in full.

Certification Timeframe

You can expect to receive your certificate 12-16 weeks after your final assignment is marked and graded, depending on the time of year. You will be provided with regular updates throughout the certification process so that you are fully informed of your individual timeframes.

Course Fees

All course fees, inclusive of all payment plans including our Premium Credit Limited option, must be settled before certification can be ordered.

*You will have access to the course for 24 months.

Assessment

The assessment process of our Data Science course consists of the following:

Assignments

The assignments for this course aim to prepare you for your next step in higher education, while providing the number of credits necessary to achieve your qualification.

At the end of each unit of study, you will need to complete an assignment which your tutor will then mark and provide you with feedback and a grade to help you to progress.

Credits

To successfully achieve this Access to Higher Education Diploma you will need 60 credits in total. The credits are split into the following two categories:

• Graded – 45 credits come from graded units, which focus on the academic subject
• Ungraded – 15 credits come from ungraded units, such as writing and study skills

As part of this Data Science diploma, UK learners will also receive help as well as guidance with their university application and the research they need to do to get the most out of their diploma.

Qualifications

Open College Network West Midlands

On successful completion of the Open College Network West Midlands Access to HE Diploma (Data Science), you will receive a QAA-recognised Access to Higher Education Diploma at Level 3 (Qualification Number: 400/1405/8). This course has also been assigned 60 credits.

Open College Network West Midlands are a national Awarding Organisation, regulated by Ofqual, the Quality Assurance Agency for Higher Education (QAA) and Qualifications Wales, to develop and award nationally recognised qualifications.

Open College Network West Midlands work in partnership with employers, training providers, colleges, universities, schools and voluntary and community organisations to offer vocational credit-based qualifications, Access to Higher Education Diplomas and quality assured Customised Accreditation that enables learners gain employment or to progress into further learning and Higher Education. They also Quality Endorse organisations internal training and skills delivery.

By completing an Access to Higher Education Diploma (Data Science) and a subsequent Data Science degree, you will open yourself up to an array of career prospects.

With Data Scientists being required in a vast range of institutions, and within multiple areas, you can tailor your career to the area that suits your interest.

You could work within:

• Artificial intelligence - Master the methods and principles specific to AI
• Data engineering - Consolidate, cleanse and structure data collected from multiple sources to build and maintain the frameworks used for analysis
• Database management and architecture - Design the digital frameworks of particular organisations
• Marketing data analysis - Measure and improve the effectiveness of marketing campaigns through analytics tools
• Machine learning - Create algorithms that work without direct human participation and can deal with large data sets

Operations data analysis - Use statistical software to evaluate and solve business-specific problems