Data is the lifeblood of a modern telecommunications business, and the organisations that know
how to work with their data — not just collect it — are the ones that outperform. This three-day
programme equips participants with the foundational and intermediate-level skills to analyse data
meaningfully, visualise it compellingly, and understand how Machine Learning and Big Data
technologies are changing what is possible. Built from first principles and progressing to real-world applications, this programme takes participants from Python basics through to building and evaluating Machine Learning models and understanding enterprise Big Data platforms. The emphasis throughout is on practice: every concept is reinforced with hands-on labs, real datasets, and exercises that mirror actual business scenarios.

WHO SHOULD ATTEND:
This programme is designed for professionals across technical and business functions who want to
develop a solid, working understanding of data science and analytics. It is ideal for:

• Business analysts and reporting professionals
• IT professionals transitioning into data roles
• Operations and strategy teams who work with data regularly
• Product managers and digital transformation professionals who need to understand data-
  driven decision making
• Fresh graduates or early-career professionals building foundational data skills
• Any professional who wants to understand how data, analytics, and Machine Learning are
  transforming modern business

PREREQUISITES:
Basic computer skills and a familiarity with spreadsheets are helpful. No prior Python, Data Science,
or Machine Learning experience is required. If you can use a laptop and have an interest in working
with data, this programme is designed for you

LEARNING OBJECTIVES:
Participants completing this programme will be equipped to:

• Understand the Data Science lifecycle and the range of roles and responsibilities within a data
  project
• Write foundational Python code for data manipulation, analysis, and automation
• Use NumPy and Pandas to load, clean, transform, and analyse structured datasets
• Perform Exploratory Data Analysis (EDA) and extract meaningful business insights
• Build data visualisations and executive dashboards using Matplotlib and Seaborn
• Understand and apply core Machine Learning concepts including supervised and
  unsupervised learning
• Build and evaluate basic ML models using Scikit-Learn
• Understand the role of Big Data technologies — Hadoop, Spark, and cloud analytics platforms

EXPECTED OUTCOMES:
By the end of the programme, participants will be able to:

• Analyse and prepare real-world datasets using Python with confidence
• Perform Exploratory Data Analysis and derive actionable business insights
• Create effective data visualisations and professional executive dashboards
• Build and evaluate basic Machine Learning models independently
• Understand the role and relevance of Big Data technologies in modern analytics architectures
• Complete an end-to-end data analysis project from raw data through to insight presentation