07 October 2026

Today

  • Reflect on your experience of the current modules.
  • Complete the mandatory Harassment and Sexual Misconduct training.
  • Check where key programme information lives.
  • Review attendance and engagement expectations.
  • Look at the assessment map and first deadline cluster.
  • Collect questions and agree one next action.

General Check-In

Today the check-in is about how the current modules are landing.

Think about Python, Computational Statistics, Visualisation, and Professional Skills. For each current module, privately mark:

  • one thing that feels clear enough to keep moving;
  • one thing that still feels unclear, slow, or effortful;
  • one independent action you can take before next week.

Then share one observation with a partner.

No one has to disclose personal circumstances in the room.

What Support Means Here

For this check-in, support does not mainly mean extra staff input.

It means identifying what kind of independent effort will help you move forward:

  • more practice with code, syntax, or errors;
  • reviewing lecture notes or workshop solutions;
  • reading documentation or examples slowly;
  • setting up a regular study routine;
  • comparing approaches with peers;
  • turning a vague worry into a specific question.

Masters study involves not knowing things yet. The useful move is to notice where effort is needed and choose the next concrete step.

Teaching staff are still happy to help you identify the right route, resource, or person to contact when you are unsure where to go.

Harassment And Sexual Misconduct Training

Sector-wide requirement linked to the Office for Students Condition E6.

It is not specific to this course and is not being run because of any concern about this cohort.

NTU requires new students to complete the online Harassment and Sexual Misconduct training by 30 October 2026.

The aim is to give everyone at NTU a shared understanding of respect, boundaries, support, and reporting routes.

What The Training Covers

The online module gives students a shared understanding of:

  • respect and boundaries;
  • harassment and sexual misconduct;
  • consent;
  • equality, diversity, and inclusion;
  • hate speech and freedom of speech;
  • reporting routes;
  • support services.

The module takes around 15-20 min.

Content Note

The training includes written examples relating to harassment and sexual violence.

It does not include explicit images or videos.

Please take care of yourself as you work through it. If you need support, contact Student Support and Wellbeing through StudentHub or the routes signposted in the module.

Complete The Training Now (15-20 mins)

Use your own laptop or phone.

Completion is tracked centrally. Tutors do not need to collect evidence from you.

If you have already completed it, use this time to check your module NOW pages and write down any practical questions.

If Anything Comes Up

You do not need to discuss personal experiences in this room.

If you want support after the module:

  • use the support and reporting routes signposted in the training;
  • contact Student Support and Wellbeing through StudentHub;
  • speak to me (Jens) if you are unsure where to go;
  • use emergency services or urgent university support if there is an immediate risk.

My role is to listen, help you find the right support route, not to investigate the issue in the tutorial.

Programme Navigation

Find these before you need them:

  • NOW learning rooms;
  • assessment briefs;
  • timetable updates and room changes;
  • module leader contact details;
  • tutorial materials;
  • independent study resources;
  • library and academic skills support;
  • student support routes when wellbeing, disability, or personal circumstances affect study.
  • MS Teams channels

Exercise: Find It Now

In pairs, choose one module and find:

  • the assessment brief or assessment information;
  • the module leader or lecturer contact route;
  • where announcements are posted;
  • where slides, data, or code files are kept;
  • what to do if something is missing or unclear.

Make a note of one thing that was easy to find and one thing that was not.

Attendance And Engagement

Good habits now prevent avoidable stress later.

  • Check NOW, your timetable, and module communication spaces every week.
  • If you miss teaching, use the module materials to catch up promptly.
  • For module-specific questions, start with the module NOW page, Teams space, or lecturer/module leader.
  • For personal concerns or uncertainty about where to go, contact me.
  • If circumstances affect assessment, look at the university support and consideration routes early.

Assessment And Project Map

Deadline Module Assessment or milestone
11 Dec 2026 Computational Statistics Report
08 Jan 2027 Visualization/Data Dashboards Portfolio
15 Jan 2027 Python/Machine Learning Report
01 Mar 2027 Research project Ethics deadline
19 Mar 2027 Computational Statistics Report
25 Mar 2027 Professional Skills Portfolio
09 Apr 2027 Brain, Behaviour and Cognition Written assignment
11 Jun 2027 Research project Project draft deadline
23 Jul 2027 Research project PG project submission deadline for all courses

The main point for now: project work starts long before the July submission deadline.

Exercise: First Deadline Cluster

Individually, mark:

  • which December-January assessment feels clearest;
  • which one feels least clear;
  • what information you still need;
  • one action to take this week;
  • one small habit that will make January easier;
  • how much time do you plan need for prep;
  • one project milestone that is worth keeping in view now.

Then compare in pairs.

Before Next Time

Before the next tutorial:

  • finish the mandatory training if you could not complete it today;
  • choose one module where you need to put deliberate effort this week, and block time for it;
  • check that you can find the formative or assessment information for your current modules;
  • choose one possible behavioural, psychological, social, health, cognitive, or data-science topic you might use when searching for datasets;
  • bring one question about finding or evaluating data.