Why I chose this course

I chose this course at Lancaster University due to its high ranking in analytics within the UK and Europe. What sets it apart is the invaluable support provided by the lectures, coupled with a dynamic curriculum structured into four modules per term. The intensity of the 10-week term ensures a focused and immersive learning experience.

The compulsory modules, including Operational Research, Statistics and Descriptive Analytics, Python, and Solving Forecasting, are highly beneficial in the industry. This course also provides various opportunities to drive into research areas such as forecasting, optimization, simulation, and stochastic modelling.

The kinds of learning sessions we have

In our course, the learning sessions include lectures, workshops, and seminars throughout each 10-week term.

Lectures provide theoretical aspects of modules while workshops offer a hands-on experience where we learn to use programming languages like Python and R.

The practical exercises conducted in workshops directly apply to real-life and industry scenarios, reinforcing the lecture content.

I have had seminars in Statistics. We had discussions among students, enabling us to collectively address Statistics questions and share our thoughts.

My preferred learning session is a workshop because it's practical for my learning. We have workshops almost every week. Despite the sizeable class in my course, workshops are conducted in smaller groups. This arrangement facilitates easier approaches to tutors and lecturers. Our lecturers are consistently supportive, encouraging questions and providing detailed instructions each week. The workshops serve as a practical application of lecture content and include comprehensive notes for easy recall. The step-by-step instructions and additional exercises foster a deeper understanding of the material, making the learning experience both engaging and enriching.

The optional modules I chose

I have chosen the following optional modules: Marketing Analytics, Intelligent Data Analysis and Visualization, and Transportation and Logistics. My aim is to work in the marketing industry.

About the Transportation and Logistics module: In light of the significant shifts in transportation and logistics, particularly post-COVID, I see immense value in understanding how analytics can optimise these processes. My interest in this area is fuelled by the recognition that analytics plays an essential role in reshaping logistics and transportation strategies to meet evolving global demands.

One unexpected benefit

One unexpected benefit I experienced during my course was the exposure to various modelling techniques, a skill set I initially lacked. These modelling techniques are applicable across industries for visualising datasets. The assignments have enhanced my understanding of the modules and shown me practical applications in real-life scenarios. This hands-on experience has not only solidified my grasp of the course material but has also equipped me with the confidence to apply these techniques.

Coming from a non-analytics background in my Bachelor's degree, I initially had reservations, but this course has transformed my perspective. I now feel significantly more confident about pursuing a career in analytics. The unexpected benefit of gaining proficiency in modelling techniques has enriched my learning experience and ignited a passion for the subject!

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Disclaimer

The opinions expressed by our bloggers and those providing comments are personal, and may not necessarily reflect the opinions of Lancaster University. Responsibility for the accuracy of any of the information contained within blog posts belongs to the blogger.