Introduction to Data Analysis

Course Content:

Fundamentals of Data Analysis:
Introduction to the basic concepts of data analysis, including types of data, descriptive statistics, and data collection methods.
Understanding the importance of data analysis in decision making and its impact on organizations.

Data Collection and Preparation:
Techniques for collecting data from various sources, including surveys, databases, and online sources.
Methods for data cleaning and preparation, including error removal, normalization, and data transformation for analysis.

Data Exploration and Visualization:
Tools and techniques for exploring data sets and discovering patterns and trends.
Creating effective visualizations, such as graphs, charts, and tables, to communicate insights in a clear and understandable way.

Basic Statistical Analysis:
Application of fundamental statistical techniques, including measures of central tendency, dispersion, and correlation analysis.
Use of basic statistical tests to infer and generalize results from data samples.

Introduction to Data Analysis Tools:
Familiarization with tools and software used in data analysis, such as Microsoft Excel, Google Sheets and statistical analysis tools such as R and Python.
Use of advanced functions and tools to perform complex analysis and handle large volumes of data.

Predictive Modeling and Advanced Analytics:
Introduction to basic predictive models, including linear regression and time series analysis.
Application of modeling techniques to make predictions and trend analysis based on historical data.

Interpretation of Results and Decision Making:
Development of skills to interpret data analysis results and draw meaningful conclusions.
Application of data insights in strategic and operational decision making within an organization.

Ethics and Privacy in Data Analysis:
Ethical considerations in the collection, analysis, and use of data, including privacy protection and compliance with legal regulations.
Best practices to ensure responsible and ethical use of data in analysis and decision making.

Practical Project:
Participants will conduct a hands-on project involving the collection, preparation, analysis and visualization of a real or simulated data set.
The project will be reviewed and evaluated, with detailed feedback from experts in data analysis.

Additional Benefits:

Data Analytics Certification:
Upon completion of the course, you will receive an industry-recognized certification that validates your ability to perform effective data analysis.

Access to Exclusive Tools and Resources:
You’ll get access to data analytics software, advanced tutorials and project templates to facilitate your learning and practical application.

Mentoring and Networking:
During the course, you will have the opportunity to interact with expert data analytics mentors and participate in networking events with other industry professionals.

Course duration: 4 months

Modality: 100% online, with live sessions and access to recorded content.