Apply here

or copy and paste this link in your browser: https://forms.gle/XGrsyAkqVJ5Fpv1JA






Background
On behalf of the German Federal Ministry for Economic Cooperation and Development (BMZ), GIZ implements the projects of "FAIR Forward - Artificial Intelligence for all" and "Data Economy". These projects have joined forces to create the AI and Data Science Bootcamp for women in South Africa, which intends to address the gender imbalance in fields of Artificial Intelligence (AI) and Data Science.

Currently less than a quarter of AI professionals globally are women. Following this trend, only 23% of tech jobs are held by women in South Africa (Women in Tech ZA). This often leads to biased data and AI based services because the experiences of women and other vulnerable groups are not represented during the development stages of these technologies. Data and AI is becoming more pervasive in its use (e.g., job applications, security checks) and the biased development of data and AI based services will exacerbate if left unchecked.

As part of its premise of democratizing AI, FAIR Forward intends to address the gender imbalance of Artificial Intelligence professionals with a tailored training on AI for women who have no prior experience on coding. Similarly, Data Economy intends to promote a human-centred data-driven economy by strengthening data awareness as well as increasing data science competencies and business models knowledge of women in South Africa.

The AI and Data Science bootcamp aims to provide AI, Data Science and business skills to women through gender responsive implementation. It will focus on creating awareness on the possible gender and diversity biases and how to address them with an intersectional lens. Specifically, FAIR Forward and Data Economy aim to increase the number of South African women having skill in the field of Data Science and AI and their development in ethical societal, development and business practices. Moreover, it is expected to contribute to the better local use of public goods in the AI sector in the medium and long term, as well as to more inclusive data and digital economies.

The course is designed for women who have basic digital skills and who use digital applications. It offers an opportunity to women of any background, 18 years and older, who reside in South Africa and who are unemployed and looking to develop skills in computer programming, AI and data science field.



with training provided by experts from: University of South Africa's (UNISA) School of Computing, Arpeggio Consulting, Move Beyond Consulting (MBC)

Training providers







Training Content and Expected Outcomes


Module
Module Name
Expected Outcomes
Module 1 Coding Basics with Python 1. Be able to program in python using fundamental programming constructs.
2. Be introduced to a set of projects from which students will choose and work in teams throughout the bootcamp.
Module 2 Data & Statistical Analysis 1. Be introduced to basic statistics;
2. Be introduced to analysis of data with python;
3. Use knowledge and skills acquired in Module 1 and Module 2 to analyse data and demonstrate proficiency with statistical analysis of data;
4. Start working on team projects using knowledge gained thus far.
Module 3 Data Visualisation 1. Be able to use python data visualisation tools to display patterns, trends and outliers in data sets;
2. Apply knowledge and skills gained in Module 1 and Module 2 to analyse raw data and present it effectively.
3. Acquire skill to write scripts for data manipulation and analysis
4. Demonstrate ability to import, prepare and analyze data
5. Continue working on team projects using knowledge gained thus far.
Module 4 Data Awareness/Data Ethics 1. Be introduced to methods to collect, analyze, and access data;
2. Understand the need for data ethics in data science;
3. Demonstrate how to apply best practices in data science.
Module 5 Communication & Presentation Skills 1. Demonstrate ability to engage and connect with an audience to present and gather information and knowledge;
2. Demonstrate ability to communicate professionally with team and "clients";
3. Know to consider audience interests, motivations, priorities, and challenges when planning and presenting business pitch;
4. Build personal negotiation style;
5. Apply skills and strategies in confident and effective pitch and negotiations.
Module 6 Introduction to entrepreneurship 1. Be able to articulate what entrepreneurship means to you
2. Pitch your venture idea to investors
3. Introduced to the South African requirements for starting your own business
4. Know common project management skills and tools
5. Be introduced to corporate governance principles.
Module 7 AI ethics and bias 1. Have insight into concerns of AI today
2. Be introduced to some of the existing guidelines in AI ethics.
Module 8 Machine Learning Fundamentals 1. Be able to build simple models for some data science applications.
2. Demonstrate knowledge of predictive modelling to support decision making.
Module 9 User-centric product design (Projects) 1. Demonstrate skill in the iterative design process where focus is on the users and their needs in each phase of the design process.
2. Demonstrate teamwork.
3. Apply coding techniques to develop a practical solution.
4. Deliver a project report.
5. Do a demonstration of the working solution.
6. Present the project.




Training Schedule


Who can apply?


Attendance, Certificates


Training Venues and Logistics




Links:

GIZ Data Economy FAIR Forward Intel Unisa School of Computing Arpeggio Consulting MBC

If you have further questions or encounter any issues in the application, please reach out to Meena Lysko