3084 Development courses in Sheffield delivered Live Online

In this series we are going behind–the–scenes with established studios and hearing how they created their own brand.

In this series we invite globally respected studios to walk us through the processes and methods they employ when working with clients.

Our masterclass series goes behind the studio door and explores the processes of globally respected designers.

Our masterclass series goes behind the studio door and explores the processes of globally respected people, studios and businesses.

Our masterclass series goes behind the studio door and explores the processes of globally respected people, studios and businesses.

In this series we invite globally respected studios to walk us through the processes and methods they employ when working with clients.

In this series we invite globally respected studios to walk us through the processes and methods they employ when working with clients.

Become an MHFA Champion in just one day, gaining an understanding of common mental health issues, the confidence to advocate for awareness, the skills to recognise signs of mental ill health, and the ability to support positive wellbeing."

Python Machine Learning algorithms can derive trends (learn) from data and make predictions on data by extrapolating on existing trends. Companies can take advantage of this to gain insights and ultimately improve business. Using Python Machine Learning scikit-learn, practice how to use Python Machine Learning algorithms to perform predictions on data. Learn the below listed algorithms, a small collection of available Python Machine Learning algorithms.

Duration 2 Days 12 CPD hours This course is intended for Data Protection Officers IT Managers and Administrators Records Managers System Developers IT Security specialist Anyone who builds and develops IT systems Overview Critical data protection concepts and practices that impact IT Consumer data protection expectations and responsibility How to bake privacy into early stages of IT products and services for cost control, accuracy and speed-to-market How to establish data protection practices for data collection and transfer How to preempt data protection issues in the Internet of Things How to factor data protection into data classification and emerging tech such as cloud computing, facial recognition and surveillance How to communicate data protection issues with partners such as management, development, marketing and legal The Principles of Privacy in Technology training is the how to course on privacy and data protection practices in the development, engineering, deployment and auditing of IT products and services. Those taking the course will develop an understanding of privacy-related issues and practices in the context of the design and implementation of information and communication technologies and systems. The training is based on the body of knowledge for the IAPP?s ANSI accredited Certified Information Privacy Technologist (CIPT) certification program. Fundamentals of information privacy Reviewing the modern history of privacy Foundational privacy concepts Data protection roles and fair information practices Exploring the impacts of privacy and data protection regulations on information management Privacy in the IT environment Compliance requirements IT risks Stakeholder privacy expectations Differentiating between privacy and security Core privacy concepts Foundational elements for embedding privacy in IT Common privacy principles Data protection by design and default Privacy considerations in the information life cycle Privacy considerations throughout the stages of the information life cycle Privacy in systems and applications Examining the risks inherent in the IT environment and options for addressing them Identity and access management Credit card information and processing Remote access BYOD and telecommuting Data encryption Additional privacy-enhancing technologies in the enterprise environment Privacy techniques Strengths and weaknesses of authentication techniques Using identifiers Privacy by design Online privacy issues Unique challenges that come from online privacy issues Laws and regulations Online threats Social media E-commerce Tracking technologies Web security protocols Technologies with privacy considerations Privacy considerations associated with a variety of technologies Cloud computing Wireless IDs Location-based services ?Smart? technologies Video/data/audio surveillance Biometric recognition