Mastering Machine Learning with Python
Upskill your team in AI and Machine Learning in 10 half-day workshops over 10 weeks.
£3,495 + VAT
Interested in joining our next course?
Enrol for
September 2024
One data apprentice can create real business impact
£1.4m revenue
identified through data-driven insights
£120,000 saved
by creating efficiencies
90% shorter project times
achieved through automations
5x faster ML model training
achieved through automations
Build capability to create and maintain key data infrastructure
Want to train new talent and reskill existing employees with one of the most in-demand technical skillsets? Develop key internal capabilities to raise the usability of critical datasets in your organisation. Cambridge Spark's Level 5 Data Engineer Apprenticeship equips learners with core technical and leadership skills.
In turn, learners are able to support business functions in creating and maintaining data analytics pipelines. They build the skillset to access data in their organisation and gain an understanding of the data engineering lifecycle, data modelling and more to help organisations maximise the value of their data.
Leaners will also have the opportunity to join guest talks on technical updates from leading technology providers like Google Cloud Platform and Databricks.
Propel your organisation forward with advanced machine learning
Machine learning is at the core of AI today — which makes understanding and being able to build machine learning models a key skill for data practitioners to add to their toolkit. Tailored for teams ranging from junior data scientists to seasoned developers and researchers, this programme is the key to mastering sophisticated data manipulation and machine learning techniques with Python.
This course equips your team with that skillset by providing the foundations, introducing core machine learning concepts and by exploring various algorithms that range in complexity that they can leverage as machine learning practitioners. They'll gain hands-on experience with both discriminative and generative models, decision trees, logistic regression, neural networks, and ensemble techniques.
This practical focus ensures that your team can immediately apply their new skills to address real-world challenges, boosting their ability to identify trends, make data-driven decisions, and drive your organisation forward.
Hear from Jonathan Wagstaff, Group Head of Business Intelligence at Exertis
Hear from Jonathan Wagstaff, Group Head of Business Intelligence at Exertis
Jonathan Wagstaff
Data apprenticeships enable myself and my team to keep up-to-date with the latest.
Suitability
This course is designed for
Professionals who already have some familiarity with the world of data analysis, and who aspire to dive into, and build a career in, AI and machine learning.
Prerequisites for this course
- A basic understanding of Python syntax and data structures
- Some exposure to data cleaning and processing libraries in Python, such as Pandas and Numpy
- Familiarity with data visualisation in Python, particularly Matplotlib
What makes our programme special
Our courses are delivered entirely online through EDUKATE.AI, our cloud-based learning platform. This format ensures your team can enhance their skills without disrupting their daily responsibilities. EDUKATE.AI offers a dynamic sandbox environment for practical skill application, complete with immediate feedback on assignments that mirror real industry challenges. We prioritise a holistic learning experience, combining hands-on practice, expert guidance, and community support to set the standard for online professional development.
Real-World Practice for Accelerated Impact
EDUKATE.AI
Expert Curriculum
Flexible Fully Online Learning
Community
A real-world learning experience
The Curriculum
Our curriculum is developed by our leading faculty, composed of data scientists in leading industry positions and academics from some of the top universities in the world.
We take a modular approach to how we offer our curriculum. This course includes all of the below modules with each module being a mix of e-learning content, such as Jupyter notebooks and instructional videos, as well as live workshops.
We continuously update the modules and reiterate to incorporate the latest, in-demand skills for competitive industry.
Core Modules
Participants embark on their machine learning journey with a comprehensive introduction to the essential concepts and tools. They explore and learn to apply key concepts such as linear regression, feature engineering and dimensionality reduction, setting a solid foundation in machine learning.
Topics covered include:
- Data preprocessing for machine learning models
- Linear Regression
- Gradient descent
- Feature Engineering
- Dimensionality reduction
Number of workshops: 4
Number of assignments: 2
Participants advance their machine learning skills by delving into one of the major types of machine learning used in industry today: supervised learning. In this module, your team will explore an array of supervised learning models that they can use, learn how to evaluate their models, and then refine them to boost performance.
Topics covered include:
- Various machine learning algorithms including: Logistic regression, K-Nearest Neighbours, Naive Bayes and Decision trees
- Binary and Multiclass classification
- Model evaluation for classification and regression algorithms
Number of workshops: 4
Number of assignments: 5
Propel your team's machine learning expertise to new heights with an exploration of neural networks and ensemble techniques. This module is crafted to give participants an introduction to these two major advanced concepts in machine learning, preparing them for the challenges of implementing more complex models in future.
Topics covered include:
- Bias and variance
- Ensemble methods: Bagging, Boosting, Stacking
- Fundamentals of Neural Networks
- Training Neural Networks, including concepts such as: Loss functions, Gradient Descent, and Hyper-Parameter Optimisation
- Machine learning algorithms include: Random Forests, AdaBoost, Gradient Boosting
Number of workshops: 2
Number of assignments: 2
FAQs
What support will my team have access to throughout the course?
Apart from instructor guidance within the workshops themselves, participants benefit from peer interaction and support within the online learning platform EDUKATE.AI. They can also benefit from a one-on-one call with a trainer/mentor to guide the next steps of their upskilling journey after completing the course.
How will participants learn?
We take a blended approach to delivering our curriculum, which means participants learn through a combination of live, instructor-led interactive workshops, and self-led practical assignments where they get to put the concepts that they learned to practice.
Is this course eligible for public funding?
No, this course is instead funded directly by the learners themselves or their employers.
In funding the course directly, your team benefits from a curriculum designed with specific learning outcomes achieved over a shorter learning period and without the restrictions attached to some publicly funded options.
Please consider our longer Apprenticeships or Skills Bootcamps if you're interested in government-funded programmes.