AIRSA Resources
Download tools, templates, datasets, and guides to accelerate AI work across Africa.
Data Entry and Codebook Template (Excel)
A ready-to-use Excel workbook for recording research or survey data consistently and documenting every variable in one place. It combines a codebook, dropdown-controlled data entry, and automatic quality checks, so your dataset is clean and well documented from the start. What’s inside: README: Step-by-step instructions, colour legend, and data conventions Codebook: One row per variable, with label, description, type, units, allowed values, min and max limits, missing codes, and required status Value Labels: Codes and meanings for each coded variable, plus standard missing (-99) and refused (-98) codes Data Entry: Space for 500 records, with dropdown lists, range validation, duplicate ID detection, and a calculated BMI example column QC Checks: Automatic counts of records, duplicate IDs, missing and out-of-range values, and header mismatches Change Log: Version history for the codebook and structure Key features: Validation limits come from the Codebook, so you update them in one place. Example variables and a worked example row show the expected format and are easy to replace. Best for: Researchers, evaluators, students, M&E teams, and anyone collecting survey or study data. Format: Excel (.xlsx); no macros required.
Grant proposal template
A complete, editable grant proposal template for nonprofits, community groups, and researchers. It guides you through each section with fill-in tables, prompts, and tips, so you can write a clear, fundable proposal that answers reviewers’ scoring criteria. What’s inside: How-to guidance with pre-start and pre-submission checklists Proposal summary and one-page executive summary Statement of need with an evidence table Project description with SMART objectives and activities Work plan, timeline, and milestones Target population and outreach plan Evaluation plan with indicators, baselines, and data sources Organizational capacity, track record, and project team Budget table and budget narrative Sustainability plan and risk management Attachments and final submission checklist Best for: Nonprofits, charities, schools, researchers, and community organizations applying to foundations, government programs, or corporate funders. Format: Editable document; replace the [bracketed] prompts and adapt sections to the funder’s guidelines.
Business Plan Template
A complete, editable business plan template for startups and small businesses. It walks you through each section with fill-in tables, prompts, and tips, so you can build a plan for investors, lenders, or your own planning. What’s inside: Executive summary, company description, and problem and solution Market analysis with target customers, market size, and a competitor comparison Products and services, pricing, marketing and sales strategy Operations plan, team and management Financial plan: startup costs, three-year projections, break-even analysis, and cash flow Funding request and use of funds Risk and mitigation table and a 12-month milestone plan Appendices: supporting documents checklist and glossary Best for: Founders, small business owners, consultants, and students preparing a plan for funding, a loan application, or internal use. Format: Editable document; replace the [bracketed] prompts with your own details.
AI Training Lesson Plan & Facilitator Guide Template
A ready-to-use template for planning and delivering a 3-hour introductory AI training session. It includes a timed agenda, a facilitator script, hands-on activities, and participant handouts.
White Paper Template
This template gives you a ready-made structure for turning research, analysis or a proposal into a professional white paper. Save a copy, then work through it from front to back, replacing each [bracketed placeholder] with your own content. The grey italic prompts tell you what belongs in each section, and you delete them as you go. Start with the cover and document control. Enter the title, author, audience, date, version and classification. The title and classification also feed the running header and footer, so update them there too. Write the body in order, but save the Executive Summary for last. It should stand alone as a one-page summary of the problem, findings and recommendation. Build each section around evidence. In Findings and Analysis, lead with the insight, then show the supporting data. Add or remove findings as needed (three to five is typical), and make each recommendation traceable to a finding. Use the built-in elements. Tables, callout boxes, figure placeholders and captions are already formatted. Copy and adapt them rather than creating new ones, so the look stays consistent. Keep headings on Word’s built-in styles (Heading 1 and 2). This keeps the table of contents working and lets you restyle the whole document from the Styles pane. Finish by refreshing the contents. Right-click the table of contents and choose Update Field, then update the entire table. Then delete any unused sections and prompts, and export to PDF for distribution.
Research Proposal Template
A ready-to-use, editable Word template for structuring AI research proposals, covering objectives, methodology, ethics, timeline, budget and expected impact for Africa.
AI Impact on Jobs & Salaries (2020-2026)
An analysis-ready dataset combining self-reported AI/ML/Data salaries with occupational AI-exposure scores, built to explore how generative AI is reshaping compensation and roles. Sources Salary data: foorilla/ai-jobs-net-salaries — weekly snapshots of the aijobs.net survey, 2020–2025. License: CC0 1.0, no attribution required. AI-exposure scores: Gmyrek, P., Berg, J., Kamiński, K., Konopczyński, F., Ładna, A., Nafradi, B., Rosłaniec, K., Troszyński, M. (2025). Global Index of Occupational Exposure to Generative AI. License: CC BY — attribution required if you use the exposure-related columns. License note This dataset is released under CC BY 4.0. The salary portion (CC0) has no attribution requirement on its own, but combining it with CC BY-licensed exposure data carries that obligation forward — please cite the source above if you use the exposure columns.
AI Usage and Impact on Students & Professionals
The AI Usage and Impact on Students & Professionals dataset focuses on understanding how people use Artificial Intelligence tools in their education, work, and daily activities. The dataset includes both students and professionals, allowing us to compare their AI usage patterns and understand how AI affects different groups of users. It contains demographic information such as age, gender, country, education level, and profession, along with information about income and the type of user. The dataset also provides detailed information about AI usage behavior. It records which AI tools users prefer, such as ChatGPT, Gemini, Claude, Copilot, and other AI platforms. It also identifies the main purpose for which AI is used, including studying, coding, writing, research, data analysis, content creation, office work, and customer support. The AI_Usage_Hours_Per_Day feature helps measure how much time users spend using AI each day, while Tasks_Performed shows the types of activities they complete with AI assistance. Another important part of the dataset is measuring the impact of AI on users. Features such as Productivity_Score, Accuracy_Rating, and Satisfaction_Score help determine how users feel AI affects their work or studies. The Time_Saved_Hours_Per_Week feature can be used to investigate whether AI helps users save time. AI_Experience_Years can also help analyze whether users with more experience using AI achieve different productivity or satisfaction levels compared with beginners. The dataset can be used to perform several interesting analyses. For example, we can investigate whether professionals use AI more frequently than students, which AI tools are most popular, which professions depend more heavily on AI, and which purposes have the highest usage. We can also examine whether increased AI usage is associated with higher productivity, greater satisfaction, or more time saved. Comparisons can be made between countries, education levels, professions, and different experience levels. From a Data Science perspective, this dataset is useful because it contains both numerical and categorical variables. Numerical features such as age, income, usage hours, productivity score, satisfaction score, and time saved can be analyzed statistically, while categorical features such as gender, country, profession, AI tool, and AI purpose can be analyzed using grouping and encoding techniques. It is also suitable for Feature Engineering. New features could be created, such as Weekly_AI_Usage_Hours, Productivity_Per_Hour, High_AI_User, or AI_Cost_Per_Usage_Hour. These engineered features can provide additional insights and can later be used as inputs for machine-learning models. Overall, this dataset provides a practical way to study the adoption, usage, and impact of Artificial Intelligence among students and professionals. It can take you through a complete Data Science workflow, starting from data inspection and cleaning, followed by EDA, visualization, feature engineering, statistical analysis, and eventually machine learning.
AI Models Pricing & Price History 2023-2026
How much does AI cost, and how fast is it getting cheaper? This dataset covers 4,403 AI model listings (2,138 unique models from 51 developers, served by 133 API providers) as of September 2026, plus a weekly price history from September 2023 to September 2026 (167,787 rows). It includes the latest models such as GPT-6, Claude Opus 5.5, Gemini 3.8, Grok 4.7, DeepSeek V4.1 and Qwen 3.8, alongside older models going back to GPT-3.5.
Generative AI HandBook
The Generative AI Handbook, authored by James Mane, provides a practical introduction to the concepts, technologies, and applications of Generative Artificial Intelligence. It explores key topics including Large Language Models, Transformer Architecture, Prompt Engineering, Retrieval-Augmented Generation, and AI model customization. The handbook introduces different generative models and explains how they create text, images, audio, video, and computer code. It examines real-world applications of Generative AI across education, healthcare, finance, business, marketing, and software development. It also emphasizes responsible AI practices, safety, and effective prompting techniques to help readers understand and apply Generative AI effectively.
Artificial Intelligence for Beginners Book
Artificial Intelligence for Beginners: A Practical, Step-by-Step Learning Guide by James Mane introduces readers to the fundamentals of artificial intelligence in clear, accessible language. It explores AI concepts, generative AI, machine learning, AI tools, and effective prompt engineering. The book demonstrates practical AI applications in education, agriculture, healthcare, business, research, and finance. It guides readers on responsible AI use, data privacy, ethics, bias, and how to verify AI-generated information. With practical exercises, mini-projects, and a 30-day learning plan, this guide equips beginners with the knowledge and confidence to use AI effectively and responsibly.
Prompt Engineering HandBook
The Prompt Engineering Handbook is a practical and professional guide to mastering the art and discipline of communicating effectively with generative AI systems. The handbook takes readers from the foundations of prompt engineering through advanced prompting techniques, professional applications, AI workflow design, evaluation, verification, privacy, responsible AI use, and governance. It provides a structured six-part prompt architecture, reusable prompt templates, practical case studies, exercises, knowledge checks, and professional audit tools that can be applied across research, education, business, programming, data analysis, writing, strategy, and creative work. The handbook also emphasises responsible AI practices, including verification, data protection, bias awareness, prompt injection defence, and human oversight. Designed for students, researchers, professionals, entrepreneurs, educators, organisations, and aspiring AI practitioners, this handbook provides a practical pathway from simply using AI to designing reliable and purposeful AI workflows. It is particularly relevant to individuals and organisations seeking to build practical AI literacy and create value through responsible AI adoption.