AIIP is a year-long programme consisting of a blended learning approach with in-person sessions held in Johannesburg, South Africa and online learning. The in-person sessions are a unique opportunity to meet with and engage in peer-learning with the professionals in the programme from various industries in a community that elevates learning from the physical and virtual classroom to tangible application in the organization and workspace.
Africa Industrial Internet Programme
A YEAR IN AIIP
4 IN-PERSON INTENSIVES*
*4 mandatory in-person intensives in Joburg and 4 webinar intensives over the duration of the course.
PYTHON AND STATISTICAL REASONING
Python is widely-used for data analysis, visualization and in application development due to its versatility, scalability and ease of learning, compared to other languages. To kick-off the programme, you will learn, or refresh, your Python programming skills in preparation for the subsequent modules. Statistics and probability concepts covered include measures of central tendency and variability, distributions and hypothesis testing.
By the end of this module, you will:
- Be able to map abstract workflows into efficient code
- Be able to understand how algorithms works in the real world inclusive of use of tools such as Github and bash, aside from the terminal
- Understand and manipulate basic data structures, flow control and requisite Python syntax
- Understand core statistical and probability concepts including descriptive statistics, distributions, statistical significance, hypothesis testing and confidence intervals
DATA ANALYTICS AND VISUALIZATION
Robust data analytics must be coupled with elegant and insightful visualizations to communicate outputs to stakeholders, regardless of dataset size. Through this module, you will learn the methods to effectively analyze data and visualize using Python libraries like numpy, matplotlib and pandas, and communicate results to different user groups.
You will be able to:
- Understand the value of exploring and visualising data before number crunching
- Distinguish between patterns in data and statistical significance
- Recognize metrics in different industry groupings and how to identify valuable metrics from vanity metrics.
- Have awareness of relational databases and how to use them
- Utilize Python libraries to analyze and visualize data
- Collaborate with peers using collaboration tools like Github
How can you leverage the immense volumes of data characteristic of industrial settings to generate business value? Machine learning is central to the identification of patterns in data, historical and real-time, and in the prediction of future outcomes with resultant cost reduction or new lucrative business models for industries. Through this module, you can learn how to build and score scalable models critical to managing the spate of data and extracting business value.
You will also be able to:
- Differentiate between classification, clustering and regression algorithms
- Deconstruct machine learning algorithms
- Select and apply the appropriate models in solving data-related problems
- Explain the criticality of accuracy, transparency, complexity and , accountability for understanding models
- Expand your programming skills further by utilizing Python machine learning tools including scikit learn
As larger volumes of data are generated, the ability to handle these large datasets becomes a prominent need in industry. In this module, you will learn how to solve unique business problems by extracting, transforming and loading datasets of varying volume,velocity and veracity. You will learn how to store data in relational and non-relational databases and handle big data on the cloud using powerful analytical services and techniques including Spark and Map-Reduce.
Fundamentally, you will learn how to:
- Visualize big data sets and build Dashboards for disseminating analytics
- Aggregate data to meaningful levels and downsample when necessary
- Be able to: interpret, apply machine learning algorithms to analyze the data, document and store big data on the cloud
INDUSTRIAL APPLICATION DEVELOPMENT
Industrial applications are central to the transformation of connected devices, data and advanced analytics into true business value; they are the backbone of the Industrial Internet. In the Industrial Application Development module, learn how to build basic industrial applications translating analytics into user-friendly interfaces conducive to the decision-making process. You will build applications using GE’s Predix platform.
You will be able to:
- Apply systems thinking in developing applications with consideration of the connectivity between sensors and assets through to data integration with applications
- Gain experience working within APIs
- Practise well-thought out technology stack choices;choose the right technology for your use case
- Design basic user interfaces suitable for your audience
- Design and deploy web applications using Python frameworks
- Acquire basic skills to build and deploy industrial applications using GE’s Predix platform
DIGITAL FOR INDUSTRIES
Learn how to create value across an organization’s businesses by driving efficiency and productivity through the adoption of the Industrial Internet. You will be introduced to the utility of having digital copies of physical assets(Digital Twins) to predict future outcomes and implement preemptive fixes to minimize downtime and associated costs. You will also learn about the utility and application of analytics to machine-generated data throughout the industrial value chain from design to installation and further using hands-on simulations and programming projects.
By the end of this module, you will be able to:
- Assess and explain the state of the industrial internet and identify trends in the African context
- Understand the industrial value chain from design to distribution, installation and beyond — Digital Thread
- Make informed decisions to improve business operations based on analytics of data generated within industrial value chain — Digital Thread
- Understand and predict physical asset performance through analysis of data generated from digital replicas — Digital Twins
- Improve factory operations by applying real-time analytics to asset data for precise, real-time decisions — Brilliant Factory
INNOVATION & INTRAPRENEURSHIP
Complement and imperative to the analytics and developer skills gained in this programme is the aptitude to breakdown abstract problems and create innovative solutions relevant to client or business needs, and to communicate clearly to diverse audiences.
In this module, you will hone your ability to:
- Identify business gaps that can be filled using sound data analytics
- Given a client problem, articulate the root problem statement as well as a well-thought out step-by-step approach to a solution
- Employ design and systems thinking to devising solutions to problems that are both innovative and practicable within the system problems are encountered.