Analysing Financial Data in Excel Training Course

This instructor-led, live training in Portugal (online or onsite) is aimed at intermediate-level advanced R users who wish to use R to build faster workflows, improve code quality, and handle more complex analysis tasks.

By the end of this training, participants will be able to: create reusable functions, improve data workflows, debug and optimize code, and produce reproducible reports.

This instructor-led, live training in Portugal (online or onsite) is aimed at business analysts who wish to automate trade with algorithmic trading, Python, and R.

By the end of this training, participants will be able to:

• Employ algorithms to buy and sell securities at specialized increments rapidly.
• Reduce costs associated with trade using algorithmic trading.
• Automatically monitor stock prices and place trades.

Big Data refers to the range of solutions designed for storing and processing extensive data sets. Originally developed by Google, these Big Data solutions have advanced and inspired numerous similar initiatives, many of which are now available as open-source projects. R has become a widely adopted programming language within the financial sector.

This instructor-led, live training in Portugal (online or onsite) is aimed at beginner-level data analysts who wish to use R programming to manipulate data, perform basic data analysis, and create compelling visualizations for insights.

By the end of this training, participants will be able to:

• Understand the basics of R Programming.
• Apply fundamental data science processes.
• Create visual representations of data.

R is a free, open-source programming language designed for statistical computing, data analysis, and graphical representation. It is increasingly utilized by corporate managers, data analysts, and researchers in academia. R has also gained popularity among statisticians, engineers, and scientists who may lack traditional programming expertise but appreciate its user-friendly interface. The language's widespread adoption stems from the growing reliance on data mining to achieve diverse objectives, such as optimizing pricing strategies, accelerating drug discovery, and refining financial models. R offers a comprehensive suite of packages tailored for data mining tasks.

This instructor-led live training in Portugal (online or onsite) is designed for data analysts wishing to program with R in SAS for cluster analysis.

By the end of this training, participants will be able to:

• Use cluster analysis for data mining.
• Master R syntax for clustering solutions.
• Implement hierarchical and non-hierarchical clustering.
• Make data-driven decisions to help improve business operations.

Data analytics serves as an essential instrument for modern business operations. This course concentrates on cultivating practical skills for hands-on data analysis, empowering participants to provide evidence-based responses to critical inquiries:

What has occurred?

• processing and analysing data
• generating insightful data visualisations

What is anticipated to happen?

• forecasting future performance
• evaluating forecast accuracy

What ought to happen?

• transforming data into evidence-driven business decisions
• optimising operational processes

This instructor-led, live training in Portugal (online or onsite) is aimed at beginner-level professionals who wish to clean and analyze data, make statistical projections, and create insightful visualizations using these tools.

By the end of this training, participants will be able to:

• Understand the basics of Python, R, Power Query, and Power BI for data analysis.
• Clean and organize datasets using Python and Power Query.
• Perform statistical analysis and projections with R.
• Create professional dashboards and reports with Power BI.
• Integrate and analyze data from multiple sources effectively.

R is a widely used, open-source environment for statistical computing, data analysis, and data visualisation. This course provides students with an introduction to the R programming language, covering its core fundamentals, essential libraries, and advanced concepts. Participants will explore advanced data analytics and graphical techniques applied to real-world datasets.

Target Audience

Developers and data analysts

Duration

3 days

Delivery Format

Lecture-based instruction combined with practical, hands-on exercises

This instructor-led, live training in Portugal (online or onsite) is aimed at anyone who wishes to learn and master the fundamentals of econometric analysis and modeling.

By the end of this training, participants will be able to:

• Learn and understand the fundamentals of econometrics.
• Utilize EViews and risk simulators.

This instructor-led, live training in Portugal (online or onsite) is aimed at intermediate-level data analysts and business professionals who wish to perform time series forecasting and automate data analysis workflows using R.

By the end of this training, participants will be able to:

• Understand the fundamentals of forecasting techniques in R.
• Apply exponential smoothing and ARIMA models for time series analysis.
• Utilize the ‘forecast’ package to generate accurate forecasting models.
• Automate forecasting workflows for business and research applications.

This instructor-led live training session, available either online or on-site, is designed for HR professionals looking to leverage analytical methods to enhance organizational performance. The curriculum encompasses both qualitative and quantitative approaches, including empirical and statistical techniques.

Course Format

• Interactive lectures and discussions.
• Numerous exercises and hands-on practice sessions.

Customization Options

• For those interested in a customized training course, please get in touch with us to make arrangements.

Target Audience

This course is designed for analysts and forecasters who wish to introduce or enhance their forecasting skills. These skills are applicable to sales forecasting, economic forecasting, technology forecasting, supply chain management, and demand or supply forecasting.

Course Description

This course guides participants through a series of methodologies, frameworks, and algorithms useful for predicting future outcomes based on historical data.

It utilises standard tools such as Microsoft Excel or open-source software (notably the R programming environment).

The principles covered in this course can be implemented using any software (e.g., SAS, SPSS, Statistica, MINITAB, ...)

This instructor-led, live training in Portugal (online or onsite) is designed for beginner to intermediate-level professionals who wish to perform statistical analysis using SPSS to interpret data accurately, run complex statistical tests, and generate meaningful insights.

By the end of this training, participants will be able to:

• Navigate the SPSS interface and manage datasets efficiently.
• Perform descriptive and inferential statistical analyses.
• Conduct t-tests, ANOVA, MANOVA, regression, and correlation analyses.
• Apply non-parametric tests, principal component analysis, and factor analysis for advanced data interpretation.

Target Audience

Course Format

Upon completing this training, participants will be equipped to:

This instructor-led live training guides participants through the process of manipulating and visualizing data using the tools available in the Tidyverse.

The Tidyverse comprises a suite of versatile R packages designed for cleaning, processing, modelling, and visualizing data. Key packages include: ggplot2, dplyr, tidyr, readr, purrr, and tibble.

• Individuals new to the R language
• Beginners in data analysis and data visualization

• A mix of lectures, discussions, exercises, and extensive hands-on practice

• Conduct data analysis and create compelling visualizations
• Derive meaningful insights from various datasets and sample data
• Filter, sort, and summarize data to address exploratory questions
• Transform processed data into informative line plots, bar plots, and histograms
• Import and filter data from diverse sources, including Excel, CSV, and SPSS files