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This two day course is designed for those who analyse data or who are creating machine learning models, but who wish to firm their understanding in core concepts as well as expanding into types of data distributions, inferential statistics (hypothesis tests), statistical significance, and a deeper understanding of how linear regression works. It is expected that you will have experience with a programming language used for data analysis such as Python or R – if this is not currently the case we suggest completing one of our Python or R for Data Handling courses.

As well as providing a business context to using core concepts such as averages, spread, and interpreting analyst visualisations, you will take this knowledge further and learn how distributions, sampling, and hypothesis testing can be used to analyse data in an organisation and in automatically highlighting significant results or anomalies.

If you are on a learning journey with Machine Learning and AI this course will give you a strong starting point in the statistical methods that underpin a large number of algorithms without overloading you with too many mathematical formulae or notations that are otherwise commonly used to communicate advanced mathematics. Your focus will be on business problems and applying tools such as Python or R that you will need as part of this journey.

If you wish to expand your understanding of Maths and Statistics related to Data Science then this course will give you all the required pre-requisite statistical knowledge needed for our more in depth programmes.

Throughout the course you will engage with practical labs, activities, and discussions with one of our technical specialists. All modules involve the use of Python or R to practice the techniques taught – setting you up to succeed in analysing, interpreting, and getting value from your data.

Minimum of GCSE Maths or equivalent
Experience with Python or R for Data Handling

Central Tendency, Variation, and Outliers

Using an appropriate software tool, calculate:
- Mean, Mode, Median, Mid-range
- Population and Sample Standard Deviation & Variance
- Inter-Quartile Range
Discuss when the above measures are appropriate
Apply methods for automating identification of outliers
Discuss appropriate handling of outliers
Practical Lab Activities with Python

Visualisations and Skew

Using an appropriate software tool, create:
- Histograms
- Scatter Plots
Use these to:
- Identify skew and the effect this may have on modelling
- Identify the location of the averages
- Compare two samples (e.g.taken at different times or fromdifferent locations)
- Determine the appropriate shape of a model and whetherthere are opportunities to linearise
Practical Lab Activities with Python

Introduction to Probability

Interpret P() notation and calculate simple and conditionalprobabilities
Use Venn diagrams with set notation to calculate probabilities
Use Tree diagrams and simple combinatorics to calculateprobabilities
Practical Lab Activities with Python

Introduction to Distributions

Recognise what a probability or data distribution is
Identify when a distributionis considered to beBinomial, Poisson,or Normal
Identify when a distribution can be treated as Normal and whatthis means for analytical methods
Practical Lab Activities with Python

Sampling

Critique different sampling techniques
Explain the impact a sampling or data gathering method mayhave on analytical model results
Recognise methods for estimating summary statistics for apopulation from a sample
Practical Lab Activities with Python

Introduction to Hypothesis Testing

Recognise the steps required for a Hypothesis test from thesetup, assumptions, testing, and interpretation of p-values
Identify a variety of tests and when they are used
Evaluate the output of tests from an appropriate software tool
Practical Lab Activities with Python

Linear Regression

Recognise when a linear regression is an appropriate method touse
Interpreting y = mx + c
Evaluate linear models
Practical Lab Activities with Python

Statistics for Data Analysis in Python Training Course in Finland

Finland is a country located in northern Europe. Helsinki is the capital and largest city of the country. The majority of the people are Finns but there is also a small Lapp population in Lapland, where the country is famous for the Northern Lights. Finland's national languages are Finnish and Swedish.

Known for its vast forests, lakes, and natural beauty, Finland is one of the world's largest producers of forest products, such as paper, pulp, and lumber. One of the world's largest sea fortresses Suomenlinna, Rovaniemi with the "White Nights", dogsled safaris and of course the Northern Lights are what makes Finland so popular for tourists. Finland is one of the best places in the world to see the Northern Lights and attracts millions of tourists during its seasons.

Finland is home to a thriving technology industry and is widely recognized as one of the world's leading technology hubs. Companies such as Nokia and Rovio (creator of the popular game Angry Birds) are based in Finland. Some of the key factors that have contributed to Finland's success in technology include; strong investment in research and development, a highly educated workforce and fundings.

Finland has a strong educational system, and is widely regarded as one of the world's most literate countries. In fact, Finland's literacy rate is one of the highest in the world, and its students consistently perform well in international tests of math and reading ability.

Also, as a pioneer in environmental sustainability, Finland is known for its efforts to reduce its carbon footprint and promote clean energy. This Nordic country is also famous for its unique and distinctive cultural heritage, including its traditional folk music and its elaborate traditional costumes.

Helsinki, Finland's capital city, is the country's business center. Helsinki is Finland's largest city, and it is home to many of the country's major corporations and organizations, including many of the country's leading technology firms. The city is also a commercial, trade, and financial center, as well as one of the busiest ports in the Nordic region.

Take advantage of our diverse IT course offerings, spanning programming, software development, business skills, data science, cybersecurity, cloud computing and virtualization. Our knowledgeable instructors will provide you with practical training and industry insights, delivered directly to your chosen venue in Finland.

Statistics for Data Analysis in Python Training in Finland

Upcoming Trainings

Statistics for Data Analysis in Python Training in Finland

Prerequisites

Outline

Upcoming Trainings