Course overview
Using industry-standard tools including Python, Jupyter Notebooks and Power BI, you develop practical data analytics and machine learning capabilities through hands-on learning and real-world datasets.
Designed to help you solve common workplace data challenges, the programme builds your ability to prepare and analyse complex data, uncover deeper insights and develop machine learning models that support forecasting and decision-making. You gain the confidence to take on more advanced analytical projects, contribute to data-driven strategy and progress into roles requiring specialist data and machine learning expertise.
Top five reasons to join this programme
Develop practical machine learning expertise
Build advanced analytics and machine learning capabilities through hands-on projects using Python, Jupyter Notebooks and Power BI.
Build highly sought-after technical skills
Gain experience in data preparation, forecasting, machine learning, natural language processing (NLP) and advanced analytical techniques that can be applied directly in the workplace.
Turn data into meaningful insights
Learn how to structure, analyse and interpret both structured and unstructured data, transforming complex information into actionable recommendations.
Move beyond reporting to predictive analytics
Develop and evaluate machine learning models, improve forecasting accuracy and support smarter, evidence-based decision-making.
Advance your career in data and AI
Gain practical, job-ready experience that can be applied immediately to live projects and help prepare you for more advanced analytics, data science and machine learning roles.
The Tees Valley Adult Skills Fund provides up to 90% funding for SMEs and up to 70% for larger organisations, for delegates who meet the required residency criteria.
Course details
What you study
Data Cleaning and Preparation for Machine Learning
Unlock the power of high-quality data, focusing on the foundations of machine learning: data cleaning and preparation. Designed for analysts, aspiring data scientists and anyone working with data, you gain practical experience of preparing real-world datasets for accurate and reliable machine learning models.
Using Power BI or Python (Jupyter Notebooks), you learn how to identify and manage missing values, remove duplicates, resolve inconsistencies, detect and treat outliers, transform and encode data, and enrich datasets for analysis. You also explore techniques for handling imbalanced data, including synthetic oversampling methods such as SMOTE.
Upon completion you are able to clean, validate, integrate and prepare data with confidence, creating a strong foundation for machine learning and advanced analytics projects.
Introduction to Machine Learning
Take your first steps into machine learning. For those who want to move beyond reporting and automation tools. Using Python, you gain practical experience building, testing and refining machine learning models while developing an understanding of the techniques used by data scientists.
You explore key concepts including regression, classification, clustering, principal component analysis (PCA), feature engineering, model evaluation and hyperparameter optimisation. You are also introduced to time-series forecasting techniques, helping you identify trends and make more informed decisions using data.
Delivered entirely using Python in Jupyter Notebooks or Visual Studio Code, you gain a practical understanding of how machine learning models work, giving you the confidence to apply them in real-world projects.
Whether you're looking to enhance your analytical skills or begin a career in machine learning, you leave with practical knowledge that can be applied immediately in the workplace.
Free Text Theme Development
Discover the value hidden within unstructured data with this practical introduction to Natural Language Processing (NLP). Designed for professionals looking to move beyond traditional reporting, you learn how to identify themes, patterns and insights from free-text data using Python.
Through a combination of theory and practical coding exercises, you learn how to clean and prepare text data, remove unwanted content, tokenise language, and apply stemming and lemmatisation techniques. You also explore topic modelling approaches, including Latent Dirichlet Allocation (LDA) and GSDMM, enabling you to analyse longer documents as well as short-form content such as survey responses, customer feedback and chat logs.
Upon completion you are able to transform large volumes of free text into meaningful themes and insights that support reporting, decision-making and machine learning initiatives.
Ideal for analysts, researchers and anyone looking to expand their data analytics toolkit into the growing field of NLP.
How you learn
The programme is delivered through a combination of on-campus workshops and dedicated one-to-one mentoring sessions. Interactive and highly practical, the sessions encourage discussion, reflection and real-world application, providing opportunities to learn from both experienced facilitators and fellow participants.
How you are assessed
With no formal assessments, this unaccredited course allows you to focus on developing practical skills without the pressure of exams, encouraging the application of knowledge directly in the workplace. You will however receive a certificate of completion and attendance as a result.
Entry requirements
Entry requirements
You are expected to:
- be a Tees Valley resident aged 19 and over, and meet the relevant legal entitlement requirements
- have a clear development pathway within your employment, such as progression into a new or more senior role, increased responsibilities, salary progression, or developing skills to meet an identified business need
- commit to engaging with the programme and completing all required documentation and reporting.
Employability
Career opportunities
Our bespoke, employer-led programmes combine practical learning with real-world application, supporting positive outcomes for both organisations and employees.
These programmes are designed for employers with identified workforce development needs and employees who are being supported to progress within their role, take on additional responsibilities, address skills gaps, or prepare for promotion and career advancement. The focus is on enabling business growth, improving productivity, and supporting workforce progression through targeted skills development.