About This Course
Qualitative research generates rich, nuanced data that, when managed and analysed rigorously, can transform the way organisations understand complex social phenomena, programme outcomes, and stakeholder experiences. Yet without the right tools and methods, large volumes of interviews, focus group transcripts, field notes, and multimedia material can quickly become overwhelming. ATLAS.ti is purpose-built to address this challenge, providing a structured environment in which researchers can import, organise, code, query, and visualise qualitative data with precision and transparency.
This ten-day programme offered by TrainingComplex delivers a comprehensive, practice-led introduction to qualitative data management and analysis using ATLAS.ti. Participants begin with the foundational principles of qualitative inquiry before progressing through every stage of the ATLAS.ti workflow — from project setup and data importation to coding, memoing, network mapping, and final reporting. Each concept is immediately reinforced through hands-on exercises using realistic datasets drawn from development, health, education, and governance contexts familiar to African and international practitioners.
The course is designed to produce analysts who can work independently and confidently within ATLAS.ti, applying both inductive and deductive coding approaches, managing inter-coder reliability, and producing outputs that meet the standards expected by donors, academic journals, and policy audiences. Participants leave with a fully developed analytical project, a personal coding framework, and the practical skills to apply ATLAS.ti to their own organisational or research mandates from the very first day back at work.
Who Should Attend
- Monitoring and evaluation officers and specialists
- Research officers and coordinators in NGOs, INGOs, and UN agencies
- Public health researchers and programme evaluators
- Academic researchers and postgraduate students
- Policy analysts and governance advisors
- Social scientists and development practitioners
- Consultants conducting qualitative assessments or reviews
- Data managers supporting research and evaluation teams
Learning Objectives
- Understand the theoretical foundations of qualitative research and their implications for data analysis
- Navigate the ATLAS.ti interface and configure projects for individual or team-based research
- Import and manage diverse data types including text documents, PDFs, audio files, images, and video
- Develop and apply inductive and deductive coding frameworks aligned to research questions
- Use ATLAS.ti memoing and annotation features to capture analytical thinking systematically
- Conduct query-based analysis using Code Co-occurrence, Boolean, and Proximity queries
- Build and interpret conceptual networks and visualisations that illustrate relationships between codes and themes
- Apply thematic, grounded theory, and framework analysis approaches within ATLAS.ti
- Manage multi-user team projects and ensure inter-coder consistency and reliability
- Link qualitative findings to quantitative variables and mixed-methods frameworks
- Produce professional reports, quotation exports, and outputs suitable for donor reporting and academic publication
- Critically evaluate the quality, rigour, and trustworthiness of qualitative analyses
Course Modules
Module 1: Foundations of Qualitative Research and Data Analysis
- Paradigms of qualitative inquiry: interpretivism, constructivism, and critical approaches
- Qualitative versus quantitative data: strengths, limitations, and complementarity
- Core qualitative methodologies: case study, phenomenology, grounded theory, ethnography, and framework analysis
- Ethical considerations in qualitative data management and participant confidentiality
- Positionality and reflexivity: how researcher identity and perspective shape data collection and interpretation
- Establishing trustworthiness in qualitative research: credibility, transferability, dependability, and confirmability
Module 2: Introduction to ATLAS.ti: Interface and Project Setup
- Overview of ATLAS.ti versions and licensing options for individuals and teams
- Navigating the ATLAS.ti workspace: project explorer, document manager, code manager, and toolbar
- Creating a new ATLAS.ti project: naming conventions, folder structure, and project settings
- Saving, backing up, and transferring ATLAS.ti projects safely
- Customising the ATLAS.ti interface: adjusting layouts, toolbars, and display preferences for an efficient workflow
- Understanding ATLAS.ti project file architecture: how documents, codes, quotations, and memos are stored and linked internally
Module 3: Data Import and Document Management
- Importing text documents, PDFs, Word files, and rich-text transcripts into ATLAS.ti
- Adding audio, video, image, and geo-referenced data as primary documents
- Organising documents using document groups, smart groups, and descriptive metadata
- Managing large document sets: versioning, linking, and maintaining an audit trail
- Applying consistent file naming conventions and metadata schemas to support systematic retrieval across the project lifecycle
- Preparing and cleaning raw data before import: transcript formatting standards, anonymisation procedures, and file compatibility checks
Module 4: Developing a Coding Framework
- Understanding the difference between inductive (emergent) and deductive (a priori) coding
- Designing a codebook: code names, definitions, inclusion and exclusion criteria, and examples
- Creating codes and code groups in ATLAS.ti manually and from existing codebooks
- Aligning the coding framework to research questions, evaluation frameworks, and theories of change
- Iterative codebook development: piloting the framework on a subset of data and refining definitions before full-scale application
- Documenting the provenance and rationale of each code to support transparency, replication, and team onboarding
Module 5: Applying Codes: Segment Selection and Annotation
- Selecting and highlighting quotations in text, audio, image, and video documents
- Assigning single and multiple codes to quotations using drag-and-drop and right-click methods
- Using in-vivo coding to capture participant language directly
- Annotating quotations and adding comments to preserve interpretive context
- Applying continuous and segment-based coding strategies to manage varying levels of analytic granularity
- Reviewing coded segments in the Quotation Manager during coding to monitor consistency and prevent code drift
Module 6: Memoing and Analytical Documentation
- The role of memos in qualitative analysis: theoretical, methodological, and reflective memos
- Creating, linking, and organising memos in ATLAS.ti
- Linking memos to codes, quotations, and documents to build a transparent reasoning trail
- Using memos to track emerging themes and draft analytical narratives
- Establishing a memo-writing discipline: timing, frequency, and structure conventions that sustain an auditable analytical journal
- Using free memos as a space for literature dialogue: connecting emerging findings to theoretical frameworks and prior research
Module 7: Advanced Coding Techniques and Code Refinement
- Merging, splitting, and renaming codes as the analysis matures
- Hierarchical coding: creating parent codes, child codes, and code families
- Reviewing and revising coded segments for consistency and accuracy
- Calculating and interpreting code frequencies and coverage statistics
- Conducting a systematic code review session: using code comments, sort functions, and colour-coding to identify redundancy, overlap, and gaps
- Saturating and retiring codes: recognising when a code category is theoretically complete and documenting closure decisions in the codebook
Module 8: Querying and Exploring Data
- Using the Quotation Manager to retrieve and review coded segments systematically
- Building Code Co-occurrence queries to identify patterns of overlap between themes
- Applying Boolean (AND, OR, NOT) and Proximity queries to test analytical hypotheses
- Using the Query Tool to filter results by document group, code group, or metadata
- Saving and re-running queries as the dataset grows to track how patterns evolve across iterative rounds of analysis
- Interpreting query outputs critically: distinguishing statistically frequent co-occurrences from analytically meaningful conceptual relationships
Module 9: Network Views and Conceptual Mapping
- Creating network views to visualise relationships between codes, quotations, and memos
- Using relationship types: is associated with, is a, is cause of, contradicts, and custom relations
- Interpreting network maps as analytical outputs and communication tools
- Exporting and embedding network diagrams in reports and presentations
- Building iterative network views that evolve across analysis phases to reflect the growing complexity of the conceptual model
- Using network views collaboratively in team settings to facilitate consensus on theme definitions and inter-concept relationships
Module 10: Team Projects and Inter-Coder Reliability
- Setting up and managing multi-user ATLAS.ti team projects and merged projects
- Assigning coding tasks and tracking coder contributions across a shared codebook
- Calculating inter-coder agreement using Cohen's Kappa and percentage agreement approaches
- Resolving coding discrepancies through consensus meetings and codebook revision
- Designing a team coding protocol: specifying segment-selection rules, double-coding sample size, and escalation procedures for ambiguous data
- Maintaining a shared codebook changelog to record all definition revisions, merges, and additions agreed upon during the team analysis process
Module 11: Thematic Analysis and Framework Analysis in ATLAS.ti
- Applying Braun and Clarke's six-phase thematic analysis process within ATLAS.ti
- Using the Framework Analysis matrix approach for structured policy and evaluation research
- Moving from codes to sub-themes, themes, and overarching analytical categories
- Documenting and justifying analytical decisions for auditability and peer review
- Distinguishing semantic from latent themes: moving beyond surface description to interpret underlying assumptions and meanings in the data
- Using the ATLAS.ti theme summary table to compile representative quotations, analytical notes, and cross-document evidence for each theme
Module 12: Mixed Methods Integration and Data Linking
- Linking qualitative ATLAS.ti findings to quantitative datasets and statistical outputs
- Using ATLAS.ti variables and attribute tables to stratify analysis by demographic or programme factors
- Integrating ATLAS.ti results with survey findings using joint displays and mixed-methods matrices
- Reporting integrated findings that honour both qualitative depth and quantitative breadth
- Designing a mixed-methods integration protocol: specifying the point of interface, direction of integration, and weighting of each data strand
- Using negative case analysis within ATLAS.ti to identify qualitative findings that challenge, nuance, or explain unexpected quantitative results
Module 13: Reporting, Exporting, and Presenting Qualitative Findings
- Exporting coded quotations, code reports, and memos for use in Word and Excel
- Structuring a qualitative findings chapter or evaluation section: logic, flow, and use of evidence
- Selecting and presenting illustrative quotations ethically and effectively
- Peer-presenting final analytical projects and receiving structured facilitator and peer feedback
- Tailoring qualitative reports for different audiences: academic write-ups, practitioner briefs, and funder evaluation reports requiring different levels of methodological detail
- Embedding reflexivity statements and methodological transparency sections to meet quality standards for qualitative publication and external audit
Requirements & Prerequisites
Participants should have a basic understanding of qualitative research concepts and experience collecting qualitative data such as interview transcripts or focus group notes. Prior exposure to any qualitative or data management software is helpful but not required, as the course begins from first principles within ATLAS.ti. Each participant must bring a laptop with ATLAS.ti installed (a free 30-day trial licence is sufficient for the duration of the programme).
Training Methodology
- Guided software walkthroughs with the trainer demonstrating each ATLAS.ti function step-by-step on a projected screen before participants replicate the task on their own machines
- Hands-on coding exercises using pre-loaded qualitative datasets drawn from real-world health, governance, and development evaluation contexts
- Individual analytical project that participants develop progressively across all ten days, applying each new skill to their own or a provided dataset
- Coding consistency workshops in which small groups code the same data extracts independently and then reconcile differences to build inter-coder reliability skills
- Network-mapping sessions where participants construct and interpret conceptual diagrams linking themes, codes, and memos
- Peer review circles in which participants present their emerging analyses for structured feedback from colleagues and the facilitator
- Case study discussions exploring published qualitative research and evaluation reports to illustrate how ATLAS.ti outputs translate into final deliverables
- Daily reflection journals in which participants document key analytical decisions and methodological rationale, building habits of rigorous audit-trail keeping
Organisational Benefits
- Stronger evidence base for programme evaluations, assessments, and research reports
- Faster and more systematic processing of large volumes of qualitative data
- Improved rigour and auditability of qualitative research processes
- Greater credibility with donors, peer reviewers, and policy audiences through transparent analytical methods
- Enhanced team capacity to conduct qualitative components of mixed-methods evaluations in-house
- Reduced reliance on external consultants for qualitative data analysis
- Better integration of beneficiary voices and stakeholder perspectives into decision-making
- Consistent coding and documentation standards across research and evaluation teams
Where Is Qualitative Data Management and Analysis Using ATLAS.TI Training Offered?
This course runs in-person across: Cape Town, Mombasa, Lagos, Nakuru, Dubai, Riyadh, Kigali, Zanzibar, Dar es Salaam, Abuja, Nairobi, Pretoria, Kisumu, Johannesburg, Arusha, Naivasha, Kampala, Addis Ababa, Accra, plus Live Virtual (online) cohorts. Browse live dates for your city below.
Upcoming Schedules
| Location | Format | Dates | Price |
|---|
| Cape Town, South Africa |
In-Person |
28 Sept 2026 – 9 Oct 2026 |
USD 7,600 |
| Mombasa, Kenya |
In-Person |
5 Oct 2026 – 16 Oct 2026 |
KES 230,000 |
| Lagos, Nigeria |
In-Person |
5 Oct 2026 – 16 Oct 2026 |
USD 5,000 |
| Nakuru, Kenya |
In-Person |
12 Oct 2026 – 23 Oct 2026 |
KES 230,000 |
| Dubai, United Arab Emirates |
In-Person |
12 Oct 2026 – 23 Oct 2026 |
USD 8,200 |
| Live Virtual |
Online |
17 Oct 2026 – 6 Dec 2026 |
KES 160,000 |
| Riyadh, Saudi Arabia |
In-Person |
19 Oct 2026 – 28 Oct 2026 |
USD 9,000 |
| Kigali, Rwanda |
In-Person |
19 Oct 2026 – 28 Oct 2026 |
USD 3,800 |
| Zanzibar, Tanzania |
In-Person |
19 Oct 2026 – 28 Oct 2026 |
USD 5,000 |
| Cape Town, South Africa |
In-Person |
19 Oct 2026 – 28 Oct 2026 |
USD 7,600 |
| Dar es Salaam, Tanzania |
In-Person |
19 Oct 2026 – 30 Oct 2026 |
USD 4,600 |
| Abuja, Nigeria |
In-Person |
19 Oct 2026 – 28 Oct 2026 |
USD 5,600 |
| Nairobi, Kenya |
In-Person |
19 Oct 2026 – 28 Oct 2026 |
KES 230,000 |
| Pretoria, South Africa |
In-Person |
26 Oct 2026 – 6 Nov 2026 |
USD 6,600 |
| Kisumu, Kenya |
In-Person |
26 Oct 2026 – 4 Nov 2026 |
KES 240,000 |
+238 more dates — view live schedule →
Frequently Asked Questions
Do I need prior experience with ATLAS.ti to attend this course?
No prior experience with ATLAS.ti is required. The course begins from the very basics of the software interface and builds progressively, so participants with no previous exposure to the platform will be fully accommodated. A foundational understanding of qualitative research methods is, however, expected.
What version of ATLAS.ti is used in the training?
The course is delivered using the latest available version of ATLAS.ti for Windows. Participants using ATLAS.ti for Mac will find that approximately 95% of functions are identical, and the facilitator will flag any differences as they arise. A free 30-day trial licence available from the ATLAS.ti website is sufficient for the duration of the programme.
Will I receive a certificate upon completion?
Yes. Participants who attend all ten days and complete the course analytical project will receive a Certificate of Completion issued by TrainingComplex, confirming their training in Qualitative Data Management and Analysis Using ATLAS.ti.
Can I use my own research data during the training?
Absolutely, and this is strongly encouraged. Participants who bring their own interview transcripts, focus group notes, or other qualitative documents can apply every exercise directly to their real research, making the learning immediately relevant and leaving the course with tangible progress on an actual project.
Is this course suitable for academic researchers as well as development practitioners?
Yes. The course content and datasets are drawn from both academic and applied development contexts, making it equally relevant for postgraduate researchers, university faculty, NGO evaluators, and consultants. The analytical approaches covered — including thematic analysis, grounded theory, and framework analysis — are used across both academic and practitioner settings.
