Duration
Analytical Thinking and Scenario Planning
1 day
Overview
Participants can expect to get familiar with a comprehensive understanding of how AI and machine learning work as core technologies and a wide range of applications, including: recommendation engines, personalization, predictive analytics, and process automation. An overview of ethical or responsible AI frameworks will wrap up the day, to ensure that participants are equipped with the skills to think about how data bias, training scenarios and other factors can impact outcomes.
Beyond just application areas, participants will learn a range of innovative tools, methodologies and frameworks that can be used to ensure that products & services meet the real needs of end-users and customers. In this workshop participants learn different technologies based on real world scenarios for data science projects along with the way they can apply it in their own business. In this workshop we will have some demo with different tools like: Python, Tableau, Disco. The main Technologies described in this workshop are:
- Data Analytics, Machine Learning and Deep Learning: Analysis of data is a process of inspecting, cleaning, transforming, and modelling data with the goal of discovering useful information, suggesting conclusions, and supporting decision-making.
- Managing Data Analysis Projects: In this topic we describe the process of analysing data and how to manage that process. We discuss the iterative nature of data analysis and the role of stating a best way to define business question, exploratory data analysis, inference, formal statistical modelling, interpretation, evaluation and communication.
- Process Mining: A cutting-edge approach to discover and visualize process models from raw event data, detect the bottlenecks in process model, and provide the effective prediction and recommendations about the future activities.
- Market Basket Analysis: A series of Data Science algorithms to find if there are combinations of products or services that frequently co-occur in transactions.
- Organizational Network Analysis: To provide an x-ray into the inner workings of an organization. It is a powerful means of making invisible patterns of information flow and collaboration in strategically important groups visible.
- Social Media Analytics: A Comprehensive framework to analyse social media data and gain actionable insights about the customer behaviour and public perceptions.
Outline
- 1. Introduction to AI
- What managers should know about Data Science(DS), Artificial Intelligence (AI), and Machine Learning (ML)
- Data vs. Information vs. Actionable Insights
- Exploratory Analytics: Concept, Usage, and Techniques
- Predictive Analytics: Concept, Usage, and Techniques
- Prescriptive Analytics: Concept, Usage, and Techniques
- Recommender Systems
- How to differentiate the Data Scientists, Data Analysts, and Data Engineers?
- What is Data Democratization?
- 2. Success Stories: AI for Business Improvement
- Analytics War Rooms: interactive dashboards that help managers making data driven decisions
- Process Mining: To detect process bottlenecks in your organization and improve your business performance
- Market Basket Analysis: Predicting the purchasing behaviour of your customer
- Social Media Analytics: How your customers talk about your brand in social media?
- Organizational Network Analysis: Who are main influencers in your organization?
- Deep Learning: How Artificial Neural Networks can improve the business
- Blockchain: how big companies applied blockchain in their business
- Analytics Skill Assessment: How to have an intelligent training plan to upskill your data analytics team
- 3. Introduction to Advanced Topics and Industry 4.0
- How machine learning works?
- How to measure the accuracy of machine learning solution?
- What is deep learning? When to use it?
- Big Data and its applications
- How Block Chain works?
- An introduction to Industry 4.0
- 9 pillars of IR 4.0
- An example of augmented reality
- How to get prepared for IR 4.0
- 4. Plan a Real Analytics Project for Your Business
- Domain study and identifying the business problem
- Identifying your analytics project objective using the S.M.A.R.T method.
- What data you have or need to prepare?
- Talent Management: how to build your analytics team?
- Analytics project planning
- Mapping your business problem into analytics solution
- What elements you need in your Analytics War Room?
Programme scope, delivery arrangements and suitability are confirmed during enquiry.