• Program duration

    6 weeks 6-8 hours per week
  • Learning Format

    Live, Online, Interactive

Why Join this Program

  • icons
    University of Cambridge Edge

    Earn a Certificate of Achievement and a Digital badge.

    Earn a Certificate of Achievement and a Digital badge.

  • icons
    Hands-on Learning

    Learn from thought leaders through practical projects and case studies.
     

  • icons
    Practical Exposure

    Use BigQuery and Colab notebook to build and validate solutions.

  • icons
    Career Assistance

    Resume and profile-building assistance for highlighting your profile to recruiters.

Corporate Training

Enterprise training for teams

Programme Overview

The Big Data for Business Intelligence course provides participants with a structured learning path to understand big data analytics, machine learning applications, and business intelligence tools. Learn to transform raw data into actionable insights from big data that can improve business outcomes and facilitate data driven decision making.

Key Features

  • Develop a foundational understanding of big data analytics and business intelligence.
  • Earn a globally recognized Certificate of Achievement and digital badge from the University of Cambridge on successful completion.
  • Access discussion forums and mentorship from industry professionals in data science and AI.
  • Master data visualization for business techniques for presenting analytical findings to stakeholders.
  • Learn from experienced professionals in the field of data science and AI for business intelligence.
  • Apply machine learning algorithms to uncover business trends and predictive insights.
  • Gain proficiency in industry-standard big data analytics tools and business intelligence platforms.
  • Work on real-world case studies to apply concepts in practical business scenarios and derive AI for business intelligence.
  • Extract, process, and analyze structured and unstructured data | Use AI-driven insights to support business decision-making.
  • Build interactive dashboards and reports for business intelligence | Apply predictive analytics to optimize business performance.
  • Attend live interactive sessions with the prestigious Cambridge academics once a week

Programme Advantage

Develop a solid understanding of how to leverage big data for business intelligence, enabling you to make impactful data driven decisions and advance your business intelligence career path.

  • Programme Certificate

    UoC Advantage

    • Earn a digital badge to display on your LinkedIn profile
    • Earn a certificate of completion along with valuable Continuing Professional Development (CPD) points
    • Hands-on learning with real-world case studies & tools

Programme Details

This course takes a practical approach using BigQuery and Colab notebook to recognize business problems, obtain data as the building blocks of problem-solving, and how to use data science techniques to help understand, build, and validate possible solutions for business intelligence.

Learning Path

    • Learn how to identify and articulate the business problem that needs to be addressed and determine how data can help inform the solution.
    • Identify the main components of big data, data science, and machine learning and how they work in a practical web tech environment.
    • Explore cloud data warehouses using open big data sources, particularly Google BigQuery, to obtain and collate large datasets.
    • Also cover how AI can help you within the data collection phase, discussing synthetic data, data labelling (RAG-powered) vector search.
    • Develop a new Google Colab notebook, write and format text, and run code blocks in Python.Use basic s tatistics and visualisations with collated data—then interpret the results.
    • Experience how AI can be used to streamline data analysis, fast-track analytical tasks, and enhance visualisations. Through notes and a Colab notebook you will see generative AI models and locally hosted AI tools in action for data processing.
    • Discuss the use of regression models on collated data and implement a linear regression model and a deep neural network regression model.
    • Undertake simple analysis of regression models and explore how AI can support you bygenerating and refining code.
    • Through notes and a Colab notebook, you will see examples of debugging and optimising models, creating synthetic data to improve training sets, and supporting exploratory data analysis through RAG-powered techniques.
    • Reflect on the outcomes in the context of the original business issue requiring resolution.
    • Learn how to communicate datadriven decisions with authority to key stakeholders and you will see examples of how AI-driven approaches can accelerate your decision-making.
    • In the final week, you will revisit and discuss the end-to-end process of data-driven decisionmaking.
    • You will reflect on its application in your own context or workplace before completing the course assignment.

6+ Skills Covered

  • Big data analytics
  • Machine learning techniques
  • Data visualization skills
  • Predictive modeling
  • AIdriven decisionmaking
  • Datadriven communication

An Immersive Learning Experience

Peer to Peer engagement

Get the real classroom experience. Interact with learners and engage with mentors in real-time via Slack.

Flexi Learn

Missed a class? Access recordings to always maintain learning progress and keep up with your cohort.

Mentoring session(s)

Expert guidance sessions from mentors for doubt clarifications, project assistance, and learning support.

Learning Support

Get a dedicated Cohort Manager for all your queries and help you succeed at every learning step.

Peer to Peer engagement
Get the real classroom experience. Interact with learners and engage with mentors in real-time via Slack.
Flexi Learn
Mentoring session(s)
Learning Support

Program Advisors

  • Dr Russell Hunter

    Dr Russell Hunter

    Senior Teaching Associate, Department of Engineering

    Russell has had a varied career with research involving software engineering, image processing and edtech whilst lecturing Computer Science. He is a PhD in Computational Neuroscience researching storage and recall in biologically plausible neural networks.

prevNext

Industry Trends

The surge in data generation across sectors like healthcare, retail, finance, and manufacturing is fueling the demand for Big Data solutions and professionals skilled in big data analytics.
 

Job Icon14.9%

CAGR for the global Big Data market from 2024 to 2030.
 

Source: Grand View Research
Job Icon$862.31

Projection for the global Big Data market by 2030

Source: Grand View Research
Job Icon28.46%

CAGR of the AI market between 2024 and 2030

Source: Encord

Batch Profile

This programme caters to working professionals from a variety of industries and backgrounds; the diversity of our students adds richness to class discussions and interactions.

  • The class consists of learners from excellent organizations and diverse industries
    Industry
    IT - 50%Software - 50%
    Companies
    Cognizant
    Genpact
    Dell
    Netflix
    Bosch
    Amazon
    Nvidia

Admission Details

Application Process

The application process consists of three simple steps. An offer of admission will be made to the selected candidates and accepted by the candidates by paying the admission fee.

STEP 1

Submit Application

Tell us a bit about yourself and why you want to do this programme

STEP 2

Reserve Your Seat

An admission panel will shortlist candidates based on their application

STEP 3

Start Learning

Selected candidates can begin the program as per cohort dates

Eligibility Criteria

For admission to this programme, candidates should have:

2+ years of work experience preferred
A bachelor's degree with an average of 50% or higher marks
Knowledge of data analytics tools would be helpful

Apply Now

Program Benefits

  • Asynchronous learning model | Over 6 weeks of learning
  • Learn with academics from University of Cambridge
  • Earn a Certificate of Achievement
  • Earn Continuing Professional Development (CPD) points
  • Earn a digital badge to display on your LinkedIn profile

FAQs

  • Are ther live sessions in this programme?

    Yes, there are optional live sessions with Univeristy of Cambridge Academics. For the Leveraging Big Data program, sessions will be help on Thursdays at 5:30pm.

    Please note:

    • The timings may be subject to change based on academic availability
    • These sessions are optional and do contribute to attendance or completion criteria but we strongly recommended that you attend these as they are an important part of the learning experience. The sessions are also recorded and uploaded onto the course within 24 hours of the session being held.

  • How can I reach out for any help and support?

    General support queries: Learners can directly reach out to their admission counsellors or submit support requests via Unviersity of Cambridge contact form which ensures they are directed to the correct support team. The Technical support team operates Monday-Friday 9am-9pm UK time and will respond to all queries as soon as possible.

    We also encourage learners and prospective customers to refer to the Unviersity of Cambridge Help Centre, which includes a wide range of FAQs covering everything from course access to technical troubleshooting. This can be accessed at: https://uoconlinehelp.cambridge.org/hc/en-gb/

  • How will I get a completion certificate?

    • On successful completion of the Course, the Univerisity of Cambridge Online will issue digital credentials to you provided you have completed all Course assignments within the dates specified in the Course, achieved the necessary passing grade, met any other criteria specified in the Course Specification, and all Fees due have been paid. 
    • These digital credentials will be sharable via social media
    • Certificates of achievement do not constitute a degree or other qualification from the University of Cambridge.

  • What is the refund policy?

    Refund policy as levied by the Univeristy of Cambridge will be applicable here: 

    Refer to this link for details: https://advanceonline.cam.ac.uk/terms-of-purchase

    (a) Cancellation Period – You have a legal right to change your mind within 14 days of submitting the Application Form and receive a refund, unless the Course has started, even if the Cancellation Period is still running;

    If you provide us with written notice to cancel the Contract outside of the Cancellation Period but at least 28 days before the Course starts, you will be entitled to a full refund of the Fees you have paid.

    (b) There may be circumstances where the univeristy might need to cancel the contract and will register you to attend the Course on a different date instead. In these circumstances you will have 14 days from being notified of the cancellation of the Course and/or your registration on the revised Course date to cancel the Contract.

  • What is the Deferral Policy?

    Deferring a Course. After purchasing the Course, you may contact Cambridge to ask for deferment to a later Course subject the following conditions. You acknowledge that:

    (a) Deferments to a later Course may only be made before the current Course has reached its half way point;

    (b) Any requested deferment must be to a Course which starts within 12 months of the start date of the Course originally booked;

    (c) Deferment to a later Course is only permitted once and is subject to availability of other courses scheduled at the University’s discretion;

    (d) If you have deferred to a later Course you will not be entitled to cancel the Course and receive a refund. However, if we cancel the later Course then you will have a right to receive a refund.

    (e) In the event that the cost of the deferred Course is higher than the cost of the Course you originally booked, we may offer you the deferred Course for the same cost as the Course originally booked without any additional cost to you. You will not receive a refund of any price difference if the cost of the deferred Course is lower than the cost of the Course you originally booked; and

    (f) Any variation of Course dates will be at our discretion and we cannot guarantee that a Course will be run again in the future.

  • What are the terms and conditions of the programme?

    The terms and conditions of Univeristy of Cambridge Online will superscede Simplilearn’s TnC. Please find the relevant links here:
    • Terms of Purchase: https://advanceonline.cam.ac.uk/terms-of-purchase
    • Other course-related policies: https://advanceonline.cam.ac.uk/policies

  • Acknowledgement
  • PMP, PMI, PMBOK, CAPM, PgMP, PfMP, ACP, PBA, RMP, SP, OPM3 and the PMI ATP seal are the registered marks of the Project Management Institute, Inc.