NVivo Qualitative Data Analysis Training Course

Duration 10 days 20 modules · 65 contact hours
Level Intermediate Certificate on completion
Who attends Research Officers, Monitoring and Evaluation Specialists and others
Fee from USD 2,200 KSh 190,000 for Kenyan organisations
Where 52 cities + online See dates by city
Next start 9 Nov 2026 Course code SD-DA-052

Before you join: Participants should be comfortable working with Windows or macOS files, folders, spreadsheets and common office applications.

Dates & prices

Two start dates a month in every city, and live online on weekdays or weekends. Fees are per participant; classroom fees include tuition, materials, lunch and refreshments, and the certificate.

Suggest a date or city

Showing the next six months. Later dates, other cities and private deliveries for your team are available on request.

Course overview

Qualitative evidence is often collected through interviews, focus groups, open-ended survey responses, field notes, policy documents and case records, then left in folders, spreadsheets or unstructured reports. NVivo provides a controlled workspace for organising this material, coding it consistently, connecting evidence to participant attributes, testing patterns and producing an audit trail that can withstand review. This matters when research informs public policy, customer insight, programme evaluation, compliance investigations, employee listening or service redesign.

This course teaches participants to set up, manage and analyse qualitative projects in NVivo from initial data preparation through to defensible findings. Participants create source structures, participant classifications, codebooks, hierarchical nodes, cases, annotations and memos. They apply thematic analysis, framework analysis, content analysis and coding queries; compare perspectives by demographic, organisational or programme variables; and use matrices, charts and visualisations to interpret patterns. The course also addresses inter-coder consistency, negative-case analysis, data protection and transparent reporting.

Instruction combines focused demonstrations with guided case work using realistic qualitative datasets. Participants progressively build an NVivo project during the first week, then deepen analysis, quality assurance and reporting during the second week. They leave with a completed project structure, coded evidence, analysis queries, a reporting plan and a reusable workflow for their own studies. The final capstone requires participants to build, review and present a complete qualitative analysis from a defined evidence base.

The course is suited to researchers, evaluators, analysts, policy teams, customer insight specialists and professionals who need to turn qualitative evidence into clear, traceable findings. It is particularly useful for people moving from manual coding, spreadsheet-based analysis or ad hoc document review to a repeatable NVivo method.

What you will be able to do

  • Build an NVivo project architecture for interviews, documents, survey responses and media files
  • Prepare qualitative source data, participant metadata and import-ready file structures
  • Develop a codebook using thematic analysis, framework analysis and content analysis methods
  • Code evidence consistently using nodes, cases, relationships, memos and annotations
  • Run coding, text-search, matrix-coding and compound queries to test analytical questions
  • Compare coded findings by participant attributes, groups, time periods and programme variables
  • Assess coding quality through codebook review, inter-coder comparison and negative-case analysis
  • Produce an auditable NVivo analysis and present evidence-based findings to stakeholders

Benefits of attending

For you

  • Replace manual transcript highlighting with a structured, searchable NVivo coding workflow
  • Build defensible qualitative findings supported by direct links to source evidence
  • Produce participant comparison tables without manually reconciling multiple spreadsheets
  • Apply recognised qualitative analysis methods when planning and documenting studies
  • Present clearer evidence to research sponsors, programme managers and decision-makers

For your organisation

  • Create consistent coding and reporting practices across research and evaluation teams
  • Reduce time spent locating quotations, reconciling versions and repeating manual reviews
  • Strengthen audit trails for policy consultations, investigations and funded programme evaluations
  • Compare stakeholder perspectives by service group, geography, role or programme cohort
  • Retain reusable project templates, codebooks and analysis procedures for future studies

Course modules

20 modules over 10 days

Participants can define an analysis workflow that links research questions, evidence, coding and reporting.

  • Qualitative research questions translated into analysable evidence requirements
  • Analytical approaches: thematic, framework, content and grounded theory coding
  • Inductive and deductive coding decisions documented before source review
  • Unit of analysis selected for transcripts, cases and documents
  • Audit trail requirements from source collection through reported findings
  • NVivo workflow aligned with research design, governance and outputs

Participants can create a secure NVivo project with a logical structure and governance controls.

  • Project architecture: sources, classifications, coding structures and analytical outputs
  • NVivo interface panels, navigation views and project item properties
  • File naming conventions supporting version control and source traceability
  • Data protection controls for personal, confidential and sensitive material
  • Project descriptions, research questions and analytical assumptions recorded
  • Backup, collaboration and project handover procedures established early

Participants can prepare and import clean, analysable source materials into NVivo.

  • Transcript formatting conventions for speakers, timestamps and paragraph references
  • Document cleaning before import: headers, tables, comments and duplicates
  • Importing Word, PDF, spreadsheet, audio, video and web sources
  • Survey response imports mapped to cases and classification attributes
  • Source folders structured by collection method, cohort and fieldwork wave
  • Imported material checked against originals for completeness and readability

Participants can model participants, organisations and other units of analysis as NVivo cases.

  • Cases created for participants, organisations, sites and service users
  • Classifications distinguish people, institutions, documents and events
  • Attribute values imported from sampling frames and survey datasets
  • Case coding links each participant contribution to relevant metadata
  • Classification sheets reviewed for missing, inconsistent and sensitive values
  • Comparison groups defined before matrix coding and interpretation begins

Participants can build a codebook with clear definitions, boundaries and coding rules.

  • Codebook fields: code name, definition, inclusion and exclusion criteria
  • Parent and child nodes organised into a usable hierarchy
  • A priori codes derived from research questions and programme theory
  • Emergent codes added without losing control of coding scope
  • Code definitions tested against ambiguous quotations and edge cases
  • Framework matrices connect cases, themes and condensed summaries

Participants can code source content accurately using NVivo nodes and coding tools.

  • Selection coding applied to sentences, paragraphs and transcript turns
  • Drag-and-drop coding compared with quick coding bar methods
  • In vivo codes preserve participants' language for emerging concepts
  • Overlapping codes used when evidence supports multiple analytical claims
  • Uncoding, recoding and code merging maintain a controlled codebook
  • Coding stripes reveal applied nodes while reviewing source context

Participants can record analytical decisions and developing interpretations within the project.

  • Memos capture methodological decisions, themes and interpretive reflections
  • Annotations record local observations without altering original source text
  • Linked memos connect evidence, codes, cases and analytical questions
  • Reflexive notes distinguish participant evidence from analyst interpretation
  • Decision logs record codebook changes and reasons for revision
  • Analytical memo structures support transparent findings and recommendations

Participants can identify candidate themes and refine them against coded evidence.

  • Code frequency reviewed without treating counts as findings alone
  • Candidate themes assembled from related codes, memos and quotations
  • Theme boundaries checked against the full source context
  • Negative cases identified where evidence challenges emerging explanations
  • Code co-occurrence examined for relationships between participant experiences
  • Thematic maps drafted to show patterns, conditions and consequences

Participants can use automated NVivo features appropriately and validate their outputs.

  • Text search queries locate terms, phrases, synonyms and word stems
  • Word frequency queries identify language patterns requiring qualitative review
  • Stop words and minimum lengths adjusted for meaningful outputs
  • Autocoding by paragraph style supports structured transcript imports
  • Sentiment autocoding reviewed critically against source context and intent
  • Automated results validated through manual sampling and codebook review

Participants can construct coding queries to retrieve evidence for defined analytical questions.

  • Coding queries retrieve intersections, unions and exclusions between nodes
  • Boolean operators specify evidence meeting multiple analytical conditions
  • Proximity queries locate concepts appearing near each other
  • Scope settings restrict queries by folders, cases and source types
  • Query results saved as sets for repeatable analytical review
  • Retrieved evidence assessed for context, relevance and contradictory accounts

Participants can compare themes systematically across cases and participant groups.

  • Matrix coding queries compare themes by case classifications
  • Rows and columns designed around answerable analytical questions
  • Cell contents inspected beyond counts to assess evidential meaning
  • Cross-tab comparisons examine differences by role, location and cohort
  • Framework matrix summaries preserve case-level interpretation alongside quotations
  • Comparative findings qualified by sample size, context and coverage

Participants can organise complex evidence relationships for case-based and systems analysis.

  • Relationships model influence, sequence, disagreement and referral patterns
  • Relationship types defined consistently for case investigation and policy studies
  • Sets group sources, nodes and cases without changing classifications
  • Source links connect related records across separate evidence collections
  • Network views reveal connections among actors, themes and documents
  • Relationship evidence checked against original material before interpretation

Participants can create visual outputs that support interpretation and stakeholder communication.

  • Hierarchy charts display coding volume within node structures
  • Charts compare attribute groups using selected nodes and measures
  • Mind maps organise early concepts before formal coding begins
  • Project maps illustrate links among sources, cases and themes
  • Conceptual models express mechanisms, conditions and observed outcomes
  • Visual outputs reviewed for analytical accuracy rather than presentation alone

Participants can manage shared coding work and assess the consistency of analytical decisions.

  • Shared codebook governance assigns ownership, approvals and revision controls
  • Pilot coding samples expose unclear definitions and inconsistent boundaries
  • Inter-coder comparison identifies agreement, disagreement and coding drift
  • Cohen's kappa interpreted cautiously alongside qualitative discussion
  • Reconciliation meetings resolve differences through evidence and documented rules
  • Quality checks review uncoded material, duplicate codes and orphan nodes

Participants can develop credible findings while distinguishing evidence, interpretation and recommendation.

  • Analytical claims linked directly to coded extracts and case summaries
  • Triangulation compares interviews, documents, observations and survey comments
  • Negative-case analysis tests explanations against disconfirming evidence
  • Reflexivity statements identify analyst position, assumptions and potential bias
  • Credibility, dependability, confirmability and transferability assessed systematically
  • COREQ reporting considerations applied to interview and focus-group studies

Participants can produce clear reports that connect findings, evidence and decisions.

  • Finding statements distinguish theme descriptions from explanatory interpretations
  • Quotation selection demonstrates range, exception and evidential strength
  • Case summaries combine participant context, coded evidence and key insights
  • NVivo exports prepared for reports, slides and evidence appendices
  • Tables present themes, supporting evidence, implications and recommended actions
  • Reporting structure aligned with research questions and decision requirements

Participants can adapt NVivo methods to evaluation, consultation and policy evidence projects.

  • Theory of change translated into deductive codes and evaluation questions
  • Consultation submissions organised by respondent type, issue and recommendation
  • Programme interviews compared by delivery site, participant group and outcome
  • Policy document analysis tracks commitments, implementation barriers and evidence gaps
  • Framework analysis supports rapid yet traceable evaluation reporting
  • Stakeholder feedback findings converted into action-oriented evidence summaries

Participants can adapt NVivo methods to customer insight, employee feedback and case reviews.

  • Customer interview themes compared by journey stage and customer segment
  • Employee comments coded for drivers, concerns and improvement suggestions
  • Exit interview analysis distinguishes recurring causes from isolated incidents
  • Investigation materials organised by allegation, witness, event and evidence type
  • Chronologies connect statements, documents and relevant coded passages
  • Sensitive findings reported with confidentiality, minimisation and access controls

Participants can prepare an NVivo project for review, archival use and future reuse.

  • Project clean-up removes redundant nodes, sources and temporary queries
  • Codebook export captures definitions, hierarchy and coding governance
  • Audit trail package includes memos, query settings and decision logs
  • Source and project backups tested before transfer or archival
  • Handover notes explain project structure, assumptions and outstanding questions
  • Reusable templates prepared for future studies and recurring evidence streams

Participants can build, review and present a complete NVivo qualitative analysis with traceable findings and recommendations.

  • Research question, evidence scope and analytical approach confirmed
  • Project structure, cases, attributes and sources configured logically
  • Codebook applied, refined and documented through analytical memos
  • Queries and matrices test priority questions and comparison groups
  • Findings checked against negative cases, context and source evidence
  • Stakeholder presentation communicates themes, quotations, implications and recommendations

Exercises and examples are adapted to each cohort's sectors and roles.

What you take back to work

  1. NVivo project architecture template
  2. Qualitative codebook template
  3. Participant classification model
  4. Coding quality assurance checklist
  5. Matrix coding query plan
  6. Evidence-based findings report outline

Who should attend

  • Research Officers — need a repeatable method for analysing interviews and documentary evidence
  • Monitoring and Evaluation Specialists — need traceable findings from programme data and stakeholder feedback
  • Policy Analysts — need to compare consultation responses, submissions and field evidence
  • Customer Insight Analysts — need to identify themes and segments within customer conversations
  • HR and Employee Experience Professionals — need to analyse engagement comments, interviews and exit data
  • Compliance and Investigation Teams — need to organise case materials and document evidential patterns

Skills and tools covered

NVivo project designQualitative codingThematic analysisCoding queriesMatrix analysisEvidence reporting

Tools and standards

NVivo, Braun and Clarke reflexive thematic analysis, Framework Method, COREQ

How the course runs

Training methodology

Teaching uses short instructor briefings, live NVivo demonstrations and structured case work based on interviews, focus-group transcripts, survey comments and documents. Participants configure a project, code evidence, run queries and interpret outputs in small groups and individually. Trainer feedback focuses on codebook quality, analytical reasoning and traceability from finding to source. Scenario-based discussions address evaluation, policy research, customer insight and workplace investigations. Each participant develops an application plan for transferring the method to an active or planned work assignment.

Requirements and prerequisites

Participants should be comfortable working with Windows or macOS files, folders, spreadsheets and common office applications. They should understand the purpose of interviews, focus groups, open-ended surveys or document review, and ideally have worked with qualitative material before. Familiarity with basic research concepts such as sampling, themes and research questions is helpful. No prior NVivo experience, programming knowledge, statistical modelling background or advanced research degree is required. Participants may bring a non-sensitive sample of their own data if their organisation permits its use.

A typical training day

08:30 – 10:30First session
10:30 – 10:45Refreshment break
10:45 – 12:30Second session
12:30 – 13:30Lunch and networking
13:30 – 15:00Third session
15:00 – 15:15Refreshment break
15:15 – 16:30Workshop and daily review

Live online deliveries follow the same structure in East Africa Time, with shorter screen blocks and longer breaks.

What the fee includes

  • Instruction by a practitioner facilitator
  • Full course workbook and materials
  • Exercise files, templates and case studies
  • Refreshments and lunch on classroom deliveries
  • Certificate of completion
  • Post-course application plan

Frequently asked questions

No. The course starts with project setup, source preparation and core coding, then progresses to queries, matrices and reporting. Participants should already understand basic qualitative research concepts or have experience working with interview, survey or document data.

Bring a laptop with NVivo installed if you are attending classroom delivery, unless the venue confirms that computers are provided. You may also bring a small, non-sensitive sample of approved work data, although course datasets are supplied.

It suits professionals who analyse interviews, focus groups, consultation responses, open-ended survey comments, documents or case records. It is appropriate for researchers, evaluators, analysts, policy staff, insight teams, HR professionals and investigators.

This course concentrates on carrying out qualitative analysis in NVivo and producing traceable outputs. It covers relevant methods such as thematic and framework analysis, but it does not replace a full course in research design, sampling or fieldwork.

Participants leave with a project structure, codebook, query plan and reporting outline that can be adapted to active studies. The application planning component helps participants identify suitable source data, classifications, coding roles and quality checks.

Training runs from 08:30 to 16:30 each day, providing about 6.5 contact hours daily. The first week establishes project setup, source management and coding; the second week focuses on queries, comparison, quality assurance, reporting and the capstone analysis.

Questions about this course?

Ask about dates, fees, group bookings or running it for your team. Our training team replies by email.

Ask on WhatsApp info@skillsetdevelopment.com

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