麻豆传媒社区入口

DISCUS

Mentoring

What is mentoring?

Mentoring is a series of discussions between two people, a mentor and a mentee, aimed at supporting the development of the mentee. The mentor is usually someone who has more experience than the mentee, who can provide support and guidance for the mentee as they develop towards their own goals. (For more information see the 麻豆传媒社区入口’s guide for mentors).

Information for mentors

You do not need previous mentoring experience, although an interest in supporting students is important. Training in mentoring skills will be provided at a 2 hour online workshop and the required commitment from you will be to meet with your mentee online for approximately 1 hour every 4-6 weeks between December 2024 and September 2025.

What will I do as a mentor?

In mentoring the agenda for discussions is led by the mentee, but it is likely that you’ll be providing support on topics such as:

  • thinking about career and skills development
  • developing confidence as a Data Scientist
  • finding employment in Data Science/AI industries following the MSc programme
  • overcoming obstacles/barriers to making progress with their work and development.

As a mentor, your job is not to provide solutions or to fix issues for your mentee. Instead, in your mentoring sessions you will provide space and encouragement for your mentee to develop their own ideas and find solutions that will work for them. You will draw on your own experiences to help your mentee to consider different perspectives and options, and you will act as a ‘sounding board’ as your mentee explores the actions they want to take in their development as a data scientist.

What are the benefits?

Becoming a mentor can result in positive benefits for your own role and development such as:

  • a sense of satisfaction and value
  • opportunities to develop mentoring/listening/supporting skills
  • exchange of knowledge and current practices in Data Science/AI
  • new insights, ideas and skills that are useful for your own role
  • connections with academia.

How do I apply?

If you are interested in becoming a mentor for Data Science/AI Masters students, please contact ai@sussex.ac.uk.

The 麻豆传媒社区入口 has a priority to broaden the diversity of students graduating with Data Science and AI MSc qualifications, therefore we particularly welcome mentors from groups that are typically under-represented in Data Science/AI industries.

“The one-on-one mentorship has been amazing, insightful, and great and it has exposed me to a lot of things.”
Postgraduate student, MSc in Data Science

Information for mentees

As a mentee you are expected to commit your free time and engage meaningful in the programme. In mentoring the agenda for discussions is mostly led by the mentee.

What will I do as a mentee?

Overall, the required commitment from you will be to meet with your mentor online for approximately 1 hour every 4-6 weeks between Dec 2023 – Sept 2024. You are also expected to attend initial mentoring training session in the form of 2 hour online workshop (date to be confirmed). Be prepared to make time for your mentoring sessions and for action/reflection in between sessions.

In this role, you need to be clear and upfront about the type of support you are hoping for from your mentor. Mentees and mentors need to establish how they can work effectively together.

Always be open and honest with your mentor. Stay open to receiving and providing constructive
feedback. If it’s not working – address it.

What are the benefits?

Becoming a mentee can result in positive benefits for your development such as:

  • careers insights and guidance
  • practical problem solving and skills development
  • opportunities to reflect, plan and set goals
  • guidance and support with the MSc programme
  • improved understanding of Data Science fields and the potential applications
  • sense of enjoyment and satisfaction
  • sharing of ideas and gaining new perspectives
  • improved confidence.

How do I apply?

If you are interested in becoming a mentee, please contact ai@sussex.ac.uk.