London Business School

Business Analytics in the Age of Generative AI

London Business School

AI

Programme Content

What you Learn: Module one: The evolution of AI for business analytics and what this means for you,Understand the progression and evolution of data science from analytics to Machine Learning and more recently Generative AI,Recognise the communicative power of analytics and its role in decision-making,Consider the evidence for Generative AIs capabilities, strengths and limitations,Explore different state of the art Generative AI models and understand the importance of prompt engineering,Address concerns related to data hallucinations and the importance of verifying insights,Discuss data privacy issues with generative AI and ways to overcome related challenges,Engage practically with ChatGPT, loading data, and conversing to derive actionable insight,Module two: Crafting data narratives through visualisation,Distinguish between visualisation as a discovery tool and as a tool to communicate insights,Describe the principles of good data visualisation and some of the pitfalls,Explore chat GPT and its code interpreter capability for efficient visualisations,Understand and apply storytelling principles using data,Engage in hands-on practice of visualisation techniques with real-world datasets,Module three: Measuring the relationship between variables,Present examples on how firms generate value using supervised learning,Discuss three key applications for supervised learning: inference, prediction, classification,Understand the model of linear regression and the ordinary least squares algorithm,Quantify the relationship between variables, the notions of statistical error, confidence intervals, and p-values,Apply the model of linear regression on large real world datasets,Use the framework of linear regression to conduct AB testing,Appreciate why correlation does not imply causality,Recognise the importance of transparency and reproducibility in the hypothesis testing process, and master documentation workflow,Module four: Learning from history to predict the future,Explore relationships between multiple variables within linear regression framework,Understand how to control for confounding variables,Engage in feature engineering to enhance predictive capabilities,Become familiar with decision tree-based models and random forests,Apply linear regression techniques to make predictions,Module five: Building predictive classification models,Extend the model of linear regression to make predictions for categorical variables,Understand the fundamentals of logistic regression and the maximum likelihood algorithm,Understand risk scoring, its relevance, and how its used in classification,Master the interpretation and application of the confusion matrix, ROC (Receiver Operating Characteristic) and AUC (Area Under the Curve) metrics,Understand the challenges in prediction like overfitting and distinguish between training vs. testing datasets,Module six: Decoding data secrets: from pattern discovery to real-world application,Understand and apply nearest neighbour algorithms for various use-cases,Dive deep into clustering algorithms, focusing primarily on k-means and hierarchical clustering methodologies,Develop an understanding of how datadriven recommendation engines operate,Synthesise the skills and techniques learned throughout the course in a comprehensive capstone case,Learn how two industry experts working in different industries are leveraging analytics to make an impact

How you Learn: On this hands-on GenAI Optimisation course, youll delve deep into the world of data analytics without writing a single line of code.,Use case studies and real-world datasets to make quantitative predictions, evidence-driven recommendations, and generate high quality data visualizations.,Use the latest ChatGPT as a data scientist assistant, to help you be ready to apply tools and techniques to your own datasets with confidence.,Learn online from anywhere in the world, working through six modules at your own pace in the space of six weeks.,Engage with a diverse community of peers from many different industries and businesses, helping you build new connections and expand your network.,Take guidance from a dedicated learning manager, who will help you navigate your learning journey and reach your objectives.

Programme Benefits

Good for you: Learn to decipher and act on business data independently of data scientists by studying the latest GenAI tools,Harness the power of AI to create instant insights, enabling you to make quicker decisions,Master storytelling with compelling data visualisations and narratives that captivate and convince stakeholders,Future-proof your career by understanding and practising the latest in AI and analytics,Amplify your skills through real-world datasets and elevate your professional value
Good for Organisation: Boost autonomous decision-making by individuals, and reduce dependency on specialised teams,Gain a competitive edge by leveraging quantitative evidence-based insights, leading to agile, effective strategies,Drive efficiency and productivity by eliminating time-consuming data bottlenecks,Engage your stakeholders by presenting data in persuasive narratives, ensuring alignment and buy-in,Tangible returns on training investment as employees understand and apply AI and analytics for business outcomes

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Prashansa Uttam

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London Business School

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Business Analytics in the Age of Generative AI | LBS