Leveraging Big Data for Business Intelligence

In this course, you’ll learn to identify business problems and leverage data to inform solutions, fast-tracking the process with the use of AI. You’ll explore cloud data warehouses like Google BigQuery to gather large datasets, use Google Colab notebooks to run Python code, apply basic statistics and create visualisations. You’ll dive into regression models, including linear and deep neural networks, to analyse data. As you progress, you’ll focus on communicating data-driven decisions to stakeholders and reflect on the end-to-end process, applying your learning through a final assignment that showcases your skills.

• Module 1: How data can resolve business issues
• Module 2: Get the data
• Module 3: Basic statistics and visualisations
• Module 4: Regression models
• Module 5: Using the outcomes
• Module 6: Conclusion

By the end of the course, you will be able to:

• communicate data-driven decisions with authority to key stakeholders
• determine the main components of Big Data, Data Science and Machine Learning and how they work in a practical web tech environment
• undertake data analysis, data cleansing and data visualisation for data-driven product development to resolve strategic business issues
• interpret what the tools are telling you in terms of data trends and how to modify your approach
• strategically apply a range of data tools and methods to analyse and resolve common business issues.

On successful completion of the course, you’ll receive a certificate from the University of Cambridge, along with valuable Continuing Professional Development (CPD) points and a digital badge to display on your LinkedIn profile. These Cambridge credentials not only showcase your knowledge and expertise but also demonstrate your commitment to professional development – helping future-proof your career.

This course is designed for professionals who want to harness the power of machine learning and data science and scale it with the power of AI to drive business success. It’s for people looking to apply big data in practical, business-focused ways – whether to enhance strategy, boost productivity or make more informed decisions. While particularly relevant to roles such as the ones outlined below, the course is beneficial to anyone seeking to apply AI and data science to real-world business challenges.

• Product Managers: Learn to use data science and machine learning to inform product decisions, improve feature development and align strategies with actionable data insights.
• Strategy Planners: Gain the skills to leverage big data and machine learning to shape data-driven strategies, optimise decision-making and identify growth opportunities that drive long-term business success.

Our flexible, online courses – delivered via a world-leading learning platform – reflect the University of Cambridge experience and values, with low learner-to-tutor ratios and academically rigorous standards.

Our online learning model is designed to help you advance your skills and specialise in emerging areas that address real-world challenges. We will help you build your network through an engaging and impactful learning journey that encourages collaboration with academics and fellow learners.

Courses are delivered in weekly modules, allowing you to plan your time effectively around existing commitments. There is an optional weekly live session, which is recorded for anyone who can’t attend. The assessment criteria will be presented to you at the start of the course, so you can approach your studies with confidence and motivation, knowing exactly what’s expected of you and how to meet those expectations.

Throughout your online learning experience with Cambridge Advance Online, you’ll have digital access to a dedicated course tutor, an expert in the field, who will help steer your learning and provide you with support and guidance every step of the way.

Level of knowledge and experience

• You’ll need a good level of spoken and written English to make the most of the course (we recommend English language proficiency equivalent to an IELTS score of 7).
• Knowledge of data analytics tools would be helpful, as would a general understanding of data and data analysis.
• Experience with SQL and Python is desirable to be able to interpret the results of statistics and visualisations and undertake analysis of regression models.

Materials and equipment

• Participants will need to register for a free Google Cloud (opens in a new tab) account to access ‘BigQuery’.
• Where possible, we ensure all of our course content is compliant to Web Content Accessibility Guidelines (WCAG) and is subject to regular review. In some cases, however, our course process requires the use of proprietary third-party tools such as Google Colab, which are subject to their own accessibility compliance. If you have any individual requirements, specifically relating to the use of a screen reader, please contact us at advanceonline@cambridge.org to discuss further.
• Sufficient internet speed (2 Mbps up/down) for video streaming.
• See recommended browsers (opens in a new tab).

Access to Virtual Learning Environment
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You can ask for support from your employer to fund this learning as part of your professional development.

Our Employer Funding guide has practical tips and templates to help you feel more confident asking for funding.

If your employer is funding your course or programme, we have several payment options available, including bank transfer (BACs), credit or debit card, and PayPal.

You can request a quote or an invoice for your organisation via our online course booking form, which will include a payment date and next steps for completing your payment.