SQL

Database structure:
● Table schemas/architecture
● Creating/editing/deleting tables
● Creating/editing/deleting entries in the table

Extracting data from databases:
● Query syntax
● Data filtering
● Basic functions in queries
● Connecting tables (relationships between them)
● Internal requests

TABLEAU or POWER BI
Accessing and managing data using Tableau prep / Power Query:
● Changing and cleaning data types
● Creating new variables
● Joining tables and aggregating data

Visual familiarization with the data:
● Creating graphs
● Choosing the right visualization
● Spotting insights and trends

Detailed analysis and creation of new variables:
● Creation of new calculated fields, creation of sets and groups (calculated fields) (Tableau)
● Calculation of new tables and creation of parameters (table calculation) (Tableau and Power BI)
● Creating filters adapted to different data types (Tableau)
● Creating tables, columns, measures using the DAX language (Power BI)
Summarizing the obtained results using the dashboard and stories/bookmarks:
● Dashboard aesthetics
● Choice of colors
● Targeted data mapping

Fundamentals of programming language syntax:
● Data structures: string, integer, float, boolean, list, set, dictionary
● Conditions: if / elif / else
● Loops: for loop, while loop
● Functions: simple and anonymous. Fitting functions to data. Introduction and work with the most popular data analysis libraries (numpy, pandas, math)
● Theoretical introduction to numpy and math
● Practical work with the pandas library: data reading, transformation, management and preparation for analysis

Data visualization:
● Matplotlib: data visualization using plot, hist, bar, scatter. Configuring graphs
● Seaborn: data representation, stylistics. Statistical models (theoretical basis, practical application with the scikit-learn library)
● linear regression
● clustering
● choice trees

Final project, delivery and billing

1. Communication skills

• Active listening
• Effective communication
• Dealing with difficult customers
• Creating a connection

2. Problem solving strategies

• Problem analysis and diagnostics
• Determination of solutions
• Troubleshooting methods
• Root cause analysis of the problem
• Latest problem solving technologies
• How to get feedback from managers
• Professional development

3. Time management and organization

• Prioritization of tasks
• Workload management
• Delegation and collaboration

4. Emotional intelligence

• Understanding and managing emotions
• Empathy and compassion
• Conflict resolution
• Stress management

5. How to learn more and faster and less
to forget

•  5 minute brain exercise
• Clear your "mental fog" with these 5
  delicious brain foods
•  Learn a powerful memory technique to
  you would never miss a meeting

• The operation of artificial intelligence. How is it different from a human?
• Creating a request (Prompt). What is the difference between a good query and a bad one?
• Validation of results. Checking the received data for suitability in a specific case.
• Versioning Policy. Identification of the used software (vendor) version in the request.
• Artificial intelligence plugins in the code editor (IDE). Advantages and disadvantages.
• Generating comments using artificial intelligence.
• Creating tests with the help of a plugin.
• Code optimization with the help of a plugin.