Course description
Today, every organization is trying its best to use business analytics for its decision-making purposes. It basically includes quantitative and statistical analysis, predictive modelling, data mining, and multivariate testing. It breaks down past performances to draw the plan for the future.
Business Analytics:Data and Decisionstraining course will help you to expand your understanding of business analytics. It will teach you how to use descriptive, predictive and prescriptive analytics to identify, analyse and solve critical business problems.
Understand and explore fundamental methods, frameworks, and business analytics techniques to make sense of your data and use it to make informed business decisions. You will also explore the practical applications of the analytical frameworks you are learning.
Upcoming start dates
Upcoming start dates
Suitability - Who should attend?
Business Analytics: Data and Decisions training course, is ideal for :
- Technical managers implementing analytics in their function or organisation.
- Professionals seeking to enter into the field of analytics & data science.
- Mid-to-senior functional managers looking to improve their decision making using data.
- Consultants aiming to develop their knowledge of business analytics.
Outcome / Qualification etc.
Business Analytics: Data and Decisions training course will:
- Take you through the fundamentals of the programming language Python to help you expand your understanding of business analytics.
- It will teach you how to use descriptive, predictive and prescriptive analytics to identify, analyse and solve critical business problems.
- It will help you understand and explore fundamental methods, frameworks and techniques of business analytics to make sense of your data and use it to make informed business decisions.
Training Course Content
Day 1
Maths & Statistics Primer
- Introduction to probability theory.
- Basics of probability & statistics Probability models.
- Bayes’ rule and conditional probability.
- Total probability.
- Bayes’ rule application.
- Probability distribution.
- Binomial distribution.
- Central limit theorem.
- Manipulating normal variables.
Day 2
Python Primer
- Operating systems overview.
- Variables in python.
- Creating and managing lists.
- Numerical lists Tuples.
- Dictionaries in python.
- Boolean variables.
- Conditional variables.
- About functions.
- Python demonstration and code manipulation.
Day 3
Descriptive Analytics
- What is data?
- Data and decision making.
- Estimate statistics of a data set.
- Maximum likelihood estimation.
- Detection and quantification of correlation.
- Outliers Linear regression.
- Real-life applications.
Day 4
Predictive Analytics
- Introduction to machine learning.
- Machine learning process.
- Supervised learning Forecasting vs inference.
- Using nearest neighbours for classification problems.
- Predict outcomes in a business context using regression trees.
- Classify data using support vector machines.
- Measure similarity of data clusters.
- Predict outcomes for different clusters.
- Machine learning in the real world.
Day 5
Foundations of linear programming
- Optimisation problems.
- Production planning problem.
- Capital budgeting problem Identifying the constraints.
- The optimal solution.
- Solving the problem in Excel.
- Model business problems as linear programmes Integer programming.
- Optimisation models.
- Tricks-of-the-trade for business decisions.
- Real-life applications.
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London Premier Centre
London Premier Centre is a UK leading training provider based in London and specialises in international short courses. Our inspiring, comprehensive portfolio of more than 400 professional development courses and seminars covers a wide range of professions from Administration, Leadership,...