Our Courses

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FAQ

  • General: How much do your courses costs?

    We offer various different payment plans depending on your training needs and budget. Please refer to our specific training courses for more information, here: https://training.actuartech.com/ or contact us at [email protected] for our corporate rates.

  • General: What makes your training platform different?

    Our training platform provide training in common practical areas of data science but is focussed specifically on actuaries and insurance professionals wanting to apply data science in their fields. We provide relevant data science in the context of insurance and actuarial use cases.

  • General: Are your case studies only relevant to actuaries and insurance problems?

    We aim our case studies at actuarial & business problems and using data science techniques to solve these. In some cases the problem in question may be relevant to non insurance problems. Feel free to reach out if you need specific guidance in this area.

  • General: How long are the courses?

    In total our courses range between 8 and 16 hours of effort however we recommend you spend 2-3 hours per week on the content for the duration of your access to our platform.

  • General: What is my recommended time commitment and do you feel I can balance this with work?

    We recommend 2-3 hours per week, in addition to an hour-long weekly live lesson we offer. Depending on your level of coding experience and general interest, that may increase. We recommend supplementing our platform with personal coding. We feel one of the best ways to learn is trough hands-on training, such as exploring a dataset or experimenting with various models.

  • General: Will I always have access to the material, or will my access expire at some point? Alternatively ask if there is a time constraint on the course?

    Our basic subscription typically allow access for 3 months in total. This gives enough time to follow through the weekly Live Lessons and go through the course in your own time. Please enquire for specific subscription options: [email protected]

  • General Terms & Conditions: What are the terms and conditions of using your platform?

    Our terms and conditions are here: https://training.actuartech.com/pages/terms

  • Getting Started: I don't have any coding experience - where do I start?

    Our Foundations in R or Python courses are suited to anyone wanting to get a basic overview of R or Python and is perfect if you have no previous experience with coding or if you want a quick refresher of the basics. Access our courses here: https://training.actuartech.com/

  • Getting Started: I am experienced in programming languages and have an actuarial background - which courses would be suitable for me?

    We would recommend you start with the Case Studies. Please note that we require that you complete and pass our Assignment in the language you are experienced in before proceeding to the Case Studies.

  • Getting Started: I am experienced in data science and don't have an actuarial or insurance background - which courses would be suitable for me?

    Our Foundations in R course covers some initial actuarial concepts. Combined with the case studies you will get a good understanding of the specific actuarial skills involved in tackling the specific problem in question. You are also welcome to reach out to us for specific help on any actuarial related matters: [email protected]

  • Getting Started: What level of actuarial skills do I need?

    We recommend having a good foundation in statistics (understand mean, correlation, error measures, typical distributions, etc.) and knowledge of topics such as linear regression and generalised linear models (GLMs). We also assume knowledge of standard insurance terms such as present value, interest rates, premiums, lapses, mortality rates, reserving, sum assured, exposure, risk, policy, etc.

  • Getting Started: What are Jupyter Notebooks and how do you use it during the course?

    A Jupyter Notebook is an interactive development environment that supports coding blocks and text blocks allowing you to combine the data, coding and description of your data science pipeline all in one place. This allows users to run code and document it. Jupyter supports primarily Python, R, and Julia but supports many others through each language's respective "kernel". Please also refer to this webinar providing an introduction to Jupyter: https://www.actuartech.com/webinars/the-power-of-computational-notebooks-introducing-jupyter

  • Getting Started: Do I need access to a specific browser to use your platform?

    Our platform supports at least all the major browsers available on both Windows and Mac including certain mobile devices.

  • Technical Help: What do I do if I get stuck while doing the course?

    Please feel free to reach out to us at [email protected] or if your query is relevant to our wider community please also make use of our topic specific community forums.

  • Technical Help: Who can I contact if I experience technical difficulties?

    We recommend you start by looking at the discussion forums to start with. You are welcome to email us at [email protected] and we will get back to you as soon as we can. Please include a screenshot if appropriate of your technical query so we can assist.

  • Technical Help: Do I need R/Python/Jupyter etc installed to complete your courses?

    No, this is not required as the entire platform runs in your browser. We recommend however that you install the relevant language on to your system (with the necessary approvals required for you to do so) to get the best learning and practical experience alongside your formal training with us - we can provide assistance on how to install the relevant software successfully.

  • Technical Help: My company has certain restrictions with regards to accessing and executing external content, will I be able to access the platform?

    In some cases you may have to use your personal PC to complete the course, however feel free to put us in touch with your IT should they have specific questions regarding the security of our platform.

  • Technical Help: My internet connection can be unreliable at times. Should I be concerned since the entire experience is online?

    We recommend at least a 1 Mbps internet speed. The Notebooks themselves are not very internet-intensive but some components of the Resource Library (such as embedded videos) will require a faster internet connection to ensure a smoother user experience.

  • Technical Help: My Notebook cells do not run, what can I do?

    Try restart your Notebook by clicking the "Kernel -> Restart & Run All" shortcut button at the top of your notebook. If the problem persists, try refresh your browser window.

  • Technical Help: When I run one of the cells lower down the Notebook, I get an error - what do I do?

    Notebook cells come pre-run when you open the course. However, you cannot run the notebook with adjust code, restart the notebook by going to "Kernel -> Restart & Run All".

  • Technical Help: How do I install a specific package in my Notebook?

    Our Notebooks are set-up with a specific set of packages, called a stack (also includes the programming language version). This contains a host of relevant data science packages and some specific to certain sections. It will be updated from time-to-time to stay relevant. If you have a specific package you would like to use, let us know at [email protected] so we can research that and potentially include in the future.

  • Technical Help: What version of Python do you use?

    We use Python 3 through version 3.8x - or next latest.

  • Data Science Pipeline - You refer to the Data Science Pipeline in your courses, what is it?

    The Data Science Pipeline is a helpful framework for structuring problems. The steps include: 1. Problem Specification 2. Data Collection 3. Data Management 4. Model Building 5. Reporting and Valdiation Visualisation and data goverance & ethics underpins the pipeline and is applied across all stages. We aim to apply the framework across all courses and Case Studies.

  • Data Science Pipeline: I am used to spreadsheets and SQL to store and access our data, will your courses teach me how to integrate these with R/Python?

    We do address these both directly (accessing .csv and .xls data is taught in Foundations) and indirectly (additional resources on accessing SQL databases).. If you have specific questions please contact us on [email protected]

  • Data Science Pipeline: I have fitted a few models in R but I do not know the math behind it, are your courses very technical?

    One of our main aims is to show case how data science techniques could be applied to actuarial problems in order to gain business insights or add value. Our use cases cover some of the technical content in order for you to obtain an understanding of the data science pipeline applied to the particular problem in question. In addition our Resource Library provides a rich set of additional technical and non technical material for additional support.