/Skills Bootcamp in Data Science (with Microsoft Certification) - January 2022 (Closed)
Provided by: Northumbria University
Course Area: All areas
Course Type: Short Course
Start date: 10/01/2022
End date: 31/03/2022
Course length: 12 weeks
Subjects: Data analytics, Data science, Machine learning, Software development
Who is this Skills Bootcamp for
This Bootcamp is for anyone needing to acquire programming/coding and data science skills to make the move to their next stage in their career. Computer programming (coding) and data science skills are increasingly needed by employers in many sectors.
Modern activities now generate huge volumes of data and the management and understanding of big data are becoming increasingly important, especially for sectors that are striving to catch up with more technically advanced industries. Demand for data scientists is increasing as organisations need to understand and analyse this historical data, then develop tools and dashboards to convert it into knowledge. The core learning material is contextualised within the construction sector as it provides rich case studies of complex data general and analysis needs. This Bootcamp teaches appropriate data science technologies and techniques. These skillsets are in high demand, particularly with graduates and those in the first two years of their career so successful learners will stand out in job interviews. Leading firms are developing data-centric tools to help asset owners, designers and builders improve efficiencies and maximise the potential of this wealth of information.
The combination of the core learning material plus the Microsoft certification makes this Skills Bootcamp a winning proposition.
- Be aged 19+
- Have the right to live and work in the UK
- Agree to provide mandatory personal data and supplementary information on their employment outcomes for up to 8 months following completion of the Skills Bootcamp
- Be looking for a new role, new opportunities or increased responsibility/promotion to a different role which utilises the skills acquired through their Skills Bootcamp
- employed/self-employed, or
- career changers/returners/redeployed, or
- unemployed within the last 12 months
Employers will be able to send existing employees who meet the Skills Bootcamp eligibility requirements on this training at an impressive 70% discount. Interested employers should contact the individual Skills Bootcamp provider.
This Skills Bootcamp is applicable to those with little to no knowledge programming languages, and whilst knowledge and experience of the construction sector would be a benefit in contextualizing the case-studies and scenarios, it is not essential. This bootcamp will also act as a nice refresher for those who want to stay up to date in their skills as well as for those who would like to expand their knowledge of new tools and techniques available in Data Science and coding.
What will I learn
Learning a programming language allows you to speak the same language as the developers, or customers you are working with. Less gets lost in translation, which makes it easier for everyone to stay on the same page as far as expectations and timelines. Understanding coding creates an opportunity to mine into product or company databases, work on more strategic initiatives and think about the potential restructuring of it, turning data into real knowledge based upon historical information and lessons learned.
Attendees will develop skills to create multiple, company-wide business intelligence dashboards, provide custom datasets for everyday operations, and command a variety of processes at the console level. Essential skills for those wishing to move into data analytics for operations and business intelligence.
The course curriculum includes introduction and exploration of the following topics.
- The role of coding in the construction industry
- Data science, big data & data analytics
- Exploratory Data Analysis (EDA) and Data Visualisation
- Classical Machine Learning (ML)
- Clustering Methods
- Classification Methods, Association Rules Mining and Regression
- Programming in Python
- Deep Learning / Artificial Neural Networks
- Data management
- Data science project implementation and management
- Application examples of data science in construction
In addition, the following soft skills will be covered as required, depending upon the circumstances of the learner.
- Presentation skills
- Portfolio development
- Employability and interview skills
Throughout the twelve week programme, learners will be expected to commit to twelve hours per week for independent learning, in addition to the tutor-led lessons. During this time, learners will develop a portfolio of problem-solving exercises based on the weekly topic or a given case study / scenario and using publicly available data sets such as Kaggle. The portfolios will demonstrate understanding of the topics covered and the application of this knowledge to scenarios relevant to their current or aspirational role. Portfolio assessment will factor heavily in the overall pass grade attained by learners.Visit this course
Creating pathways to employment
How has the Skills Bootcamp been designed/created with employer input?
A steering group of employers was formed to provide input on the curriculum, use-case scenarios, and desired outcomes. The steering group met remotely to discuss the proposed content and hear from the course designers and lecturers and were subsequently invited to consider and discuss internally before providing feedback to inform the final draft of the agenda and course objectives.
How are employers involved in the delivery of this Skills Bootcamp?
Employers have been invited to provide case-studies in written and/or video format to describe an existing scenario which would benefit from internal coding resource, or an aspect of their business which they feel could be improved if they had the skills.
What are the routes to employment following successful completion?
The employer engagement strategy which is applied to this programme does not rely upon completion of the coursework and portfolio before introducing learners to prospective employers, rather that we look to match the learner to the employer at the earliest possible opportunity and refine the recruitment selection process through the duration of the course.