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Data Science: How to Plan Projects, Research and Reflect

kurs ist nicht verfügbar in Deutsch (Deutschland)

Wir übersetzen es in weitere Sprachen.

Data Science: How to Plan Projects, Research and Reflect

Dozent: Jennifer Sexton

Bei enthalten

Mehr erfahren

2 Module

Verschaffen Sie sich einen Einblick in ein Thema und lernen Sie die Grundlagen.

Stufe Mittel

Empfohlene Erfahrung

8 Stunden zu vervollständigen

Flexibler Zeitplan

In Ihrem eigenen Lerntempo lernen

Bereiten Sie sich auf einen Abschluss vor.

Mehr erfahren

2 Module

Verschaffen Sie sich einen Einblick in ein Thema und lernen Sie die Grundlagen.

Stufe Mittel

Empfohlene Erfahrung

8 Stunden zu vervollständigen

Flexibler Zeitplan

In Ihrem eigenen Lerntempo lernen

Bereiten Sie sich auf einen Abschluss vor.

Mehr erfahren

Was Sie lernen werden

How to plan a data science project using a clear framework
·How to research a topic and complete a literature review
·How to reflect on your work and communicate your findings

Kompetenzen, die Sie erwerben

Kategorie: Critical Thinking
Kategorie: Analytical Skills
Kategorie: Record Keeping
Kategorie: General Science and Research
Kategorie: Data Science
Kategorie: Technical Communication
Kategorie: Personal Development

Wichtige Details

Kürzlich aktualisiert!

Dezember 2025

Bewertungen

1 Aufgabe

Unterrichtet in Englisch

91% of learners achieved a positive career outcome

Erfahren Sie, wie Mitarbeiter führender Unternehmen gefragte Kompetenzen erwerben.

Weitere Informationen zu Coursera für Unternehmen

Logos von Petrobras, TATA, Danone, Capgemini, P&G und L'Oreal

In diesem Kurs gibt es 2 Module

This course guides you through the key steps involved in planning and delivering a successful data science project. You will learn how to define your project aims, build a clear project plan, and select methods that support strong, evidence-based work. The course also introduces core academic skills, including how to research a topic, complete a literature review, and evaluate information critically.

Reflection is a central part of the process, and you will learn how to reflect on your decisions and communicate your findings with clarity and confidence. Through practical activities and real examples, you will build the skills needed to approach data science projects in a structured and thoughtful way. By the end of the course, you will be ready to plan, research and reflect effectively on your own data science work.

Moduldetails

In this short course, you will learn to communicate the key concepts, skills and attitudes for developing a proposal to deliver data science project work, which can then be applied in the workplace.

Das ist alles enthalten

22 Lektüren1 Aufgabe

22 LektürenInsgesamt 249 Minuten

About this course10 Minuten
How to study this course10 Minuten
Short course author2 Minuten
1.1 Overview 5 Minuten
1.2 What is reflective writing and why am I being asked to do it? 10 Minuten
1.3 Why should data scientists write reflectively? 5 Minuten
1.4 A simplified model for reflective writing 25 Minuten
1.5 Shifting from reflective thinking to reflective writing 10 Minuten
1.6 Next steps 2 Minuten
2.1 A model for reflective writing – an introduction to Gibbs' model15 Minuten
2.2 The reflective template5 Minuten
2.3 When should I reflect?5 Minuten
2.4 Barriers to writing reflectively20 Minuten
2.5 Reflective activity: Examples of student reflections35 Minuten
2.6 Reflective activity: Tutor feedback on student reflections30 Minuten
3.1 Introducing CRISP-DM15 Minuten
3.2 Large projects with diverse teams5 Minuten
3.3 Day-to-day tasks5 Minuten
3.4 How do data scientists collaborate?5 Minuten
3.5 How can I use reflective writing to guide my research?10 Minuten
3.6 Reflection for different purposes within the research project context15 Minuten
Continuing your studies in Data Science5 Minuten

1 AufgabeInsgesamt 30 Minuten

3.7 Summary MCQ on CRISP-DM30 Minuten

This week is delivered in collaboration with Skills@Library and examines how to conduct an efficient literature search, keep accurate records, critique the available published literature and consolidate this information into a viable research proposal.  

Das ist alles enthalten

1 Video15 Lektüren

1 VideoInsgesamt 6 Minuten

4.3 Search tools6 Minuten

15 LektürenInsgesamt 175 Minuten

4.1 Overview of Week 22 Minuten
4.2 Deciding where to search5 Minuten
4.4 Developing a search strategy15 Minuten
4.5 Next steps 2 Minuten
5.1 Reading with a question in mind: SQ3R5 Minuten
5.2 Matching task: Using questions to guide a literature search10 Minuten
5.3 Reading to answer specific questions40 Minuten
5.4 How should I take notes?10 Minuten
5.5 Software for note taking2 Minuten
5.6 What makes a good research question?2 Minuten
5.7 Next steps2 Minuten
5.8 Annotated course bibliography10 Minuten
Continuing your studies in Data Science5 Minuten
6.1 Activity brief: Reflective assignment60 Minuten
Course Summary5 Minuten

Bereiten Sie sich auf einen Abschluss vor.

Wenn Sie Kurs von University of Leeds absolvieren, erhalten Sie möglicherweise eine Vorschau der Themen, Materialien und Lehrkräfte für einen verwandten Studiengang. So können Sie besser einschätzen, ob das Thema oder die Universität die richtige Wahl für Sie wäre.