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DI-018

The Complete Course on Data Science & Big Data Analytics

Intensive 5-day course · English, Arabic & European languages

Chief Technology Officers, research analysts and systems engineers examine quantitative data science workflows across this five-day intensive programme. Delegates explore big data architectures, work through the 6 stages of the analytical lifecycle, evaluate statistical algorithms in R, model unstructured and textual data, and deploy in-database analytics to support strategic enterprise decisions.

Classroom

Public courses in our cities

  • 19–23 Oct 2026Vienna£3,400 + VAT
  • 19–23 Oct 2026Jeddah£4,200 + VAT
  • 2–6 Nov 2026Barcelona£3,080 + VAT
  • 16–20 Nov 2026Muscat£3,080 + VAT
  • 7–11 Dec 2026Manama£3,080 + VAT
  • 21–25 Dec 2026Paris£3,600 + VAT
Show 24 more dates
  • 4–8 Jan 2027Riyadh£4,200 + VAT
  • 18–22 Jan 2027London£3,360 + VAT
  • 1–5 Feb 2027Doha£4,200 + VAT
  • 15–19 Feb 2027Istanbul£2,280 + VAT
  • 1–5 Mar 2027Geneva£4,200 + VAT
  • 15–19 Mar 2027Vienna£3,400 + VAT
  • 5–9 Apr 2027Barcelona£3,080 + VAT
  • 19–23 Apr 2027Abu Dhabi£4,200 + VAT
  • 3–7 May 2027Cairo£2,280 + VAT
  • 17–21 May 2027Paris£3,600 + VAT
  • 7–11 Jun 2027Jeddah£4,200 + VAT
  • 21–25 Jun 2027London£3,360 + VAT
  • 5–9 Jul 2027Singapore£4,200 + VAT
  • 19–23 Jul 2027Istanbul£2,280 + VAT
  • 2–6 Aug 2027Muscat£3,080 + VAT
  • 16–20 Aug 2027Vienna£3,400 + VAT
  • 6–10 Sep 2027Barcelona£3,080 + VAT
  • 20–24 Sep 2027Casablanca£2,280 + VAT
  • 4–8 Oct 2027Manama£3,080 + VAT
  • 18–22 Oct 2027Paris£3,600 + VAT
  • 1–5 Nov 2027Amman£3,400 + VAT
  • 15–19 Nov 2027London£3,360 + VAT
  • 6–10 Dec 2027Madrid£3,400 + VAT
  • 20–24 Dec 2027Istanbul£2,280 + VAT

Group discount: 2 delegates 20% · 3 delegates 35% · 5 or more delegates 50%

Can't make these dates? We can run this course for your team on dates that suit you. Ask for custom dates · In-house options

Online (live)

With a trainer, on dates to suit your team

This course can be taught live online by a trainer, in English, Arabic or any European language, for one person or a whole team.

£1,850 + VAT

Group discount: 2 delegates 20% · 3 delegates 35% · 5 or more delegates 50%

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The Complete Course on Data Science & Big Data Analytics

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Course overview

Enterprises generate voluminous data streams across transactional databases, customer channels and digital telemetry. Extracting commercial value from these feeds requires systematic data science practices rather than superficial reporting. This programme equips technical leads and quantitative analysts with the methodologies necessary to design, validate and operationalise scalable analytical models.

The curriculum traces the formal data analytics lifecycle from initial problem discovery through to live operational deployment. Delegates review architectural frameworks that differentiate traditional business intelligence from modern data science. Using statistical environments such as R, they apply exploratory methods, regression algorithms, association rules and advanced clustering to structured and unstructured corporate datasets.

Delegates examine time series forecasting, textual analysis and in-database computation. Final sessions explore data visualisation techniques and project governance, preparing analytical teams to deliver reliable corporate findings.

Course objectives

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

  1. Evaluate the commercial applications and technical architecture of enterprise big data analytics
  2. Apply the end-to-end data analytics lifecycle from discovery to operational deployment
  3. Construct statistical evaluation models in R covering regression, clustering and association rules
  4. Execute advanced analytical techniques including time series forecasting, classification and text analysis
  5. Integrate in-database analytical tools and deliver visual findings to corporate stakeholders

Who should attend

This course suits:

  • Statistical analysts, data researchers and quantitative modelling teams
  • Lead software engineers and enterprise data research specialists
  • Technology engineers, Chief Technology Officers (CTO) and Chief Information Officers (CIO)
  • Strategic development directors and commercial technology planners

Daily agenda

  1. Day 1

    Foundations of Big Data Analytics and Architecture

    • Contemporary practices, developments and industry trends in big data analytics
    • Distinguishing traditional business intelligence from computational data science
    • Designing scalable analytical infrastructure and technical architectures
    • Operational roles for data science across technology and commercial functions
    • Core commercial drivers for deploying enterprise big data programmes
    • Review session and practical big data deployment case study
  2. Day 2

    The Data Analytics Lifecycle and Phased Modelling

    • Overview of the structured data analytics lifecycle
    • Stage 1: Discovery and framing the operational business problem
    • Stage 2: Preparation, cleansing and staging of corporate datasets
    • Stage 3: Model planning, variable selection and technical review
    • Stage 4: Model creation, execution and algorithmic calibration
    • Stage 5: Developing a stakeholder communication and presentation plan
    • Stage 6: Transitioning analytical models from planning into live operation
    • Review session and lifecycle implementation case study
  3. Day 3

    Statistical Evaluation and Algorithmic Methods in R

    • Overview of the R statistical computing framework and environment
    • Foundations of high-volume data analytics and statistical sampling
    • Conducting structured exploratory data analysis
    • Statistical evaluation techniques and hypothesis validation methods
    • Advanced algorithmic clustering methods for pattern discovery
    • Theory and mathematical implementation of association rules
    • Linear, multiple and logistic regression modelling techniques
    • Review session and statistical modelling case study
  4. Day 4

    Advanced Analytical Theory and Machine Learning

    • Algorithmic theory and techniques for multi-class classification
    • Time series analysis, trend decomposition and sequential forecasting
    • Textual analysis, natural language parsing and unstructured mining
    • Selecting appropriate enterprise software tools for advanced analytics
    • Practical use-case evaluation and model performance assessment
    • Review session and applied machine learning case study
  5. Day 5

    In-Database Analytics, Project Governance and Reporting

    • Processing, extracting and analysing unstructured corporate data
    • Executing high-performance in-database analytics across large repositories
    • Integration workflows for embedding analytics into operational systems
    • Management best practice and governance for analytical project delivery
    • Designing effective data visualisations and executive reporting summaries
    • Review session, case study evaluation and course summary

Certificate

Every delegate who completes the course receives an ARUK Training Certificate of Attendance.

Frequently asked questions

How do I register?

Choose a date and city in the schedule and press Register, or send us an enquiry. Our team confirms your place and sends an invoice.

Are fees shown with VAT?

Fees are shown per delegate and exclude VAT, which is added to the invoice where applicable.

Can this course be delivered for our team only?

Yes. Any ARUK course can be delivered in-house at your premises, in a meeting room we book for you, or 1-to-1.

Is this course available online?

Yes. We run it live online with a trainer, on dates that suit your team, for £1,850 + VAT per delegate.

Is there a group discount?

Yes. 20% for 2 delegates, 35% for 3 delegates and 50% for 5 or more delegates on the same course.

Can the course be delivered in Arabic or another language?

Yes. Our courses can be delivered in English, Arabic or any European language, by a trainer who teaches in that language. Mention your preferred language when you register or enquire.

What certificate will I receive?

An ARUK Training Certificate of Attendance.

Related courses

Register

The Complete Course on Data Science & Big Data Analytics

Key booking terms (read before you register)
  • The full fee is paid in advance, before the course starts.
  • Cancel in writing 30 or more days before the start date (45 for in-house) for a refund. Later than that, the full fee is payable.
  • No refund for non-attendance or partial attendance.
  • Places are for the named delegate only; another person cannot attend instead.
  • Moving to another date or city is only possible if ARUK agrees in writing.
  • Travel, accommodation and visas are your responsibility. A refused visa does not change the cancellation terms.

booking terms and conditions

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The Complete Course on Data Science & Big Data Analytics