Python, SQL and data analytics

First, you will learn Python, a scripting language that can be used to write tools for data extraction and transformation, and the structure of relational databases with SQL. You will then learn how to evaluate data sets and visualize the results, as well as how to use dashboards, text mining and AI in a professional environment.
  • Certificates: Python" certificate
    Certificate "Relational Databases SQL"
    Data Analytics" certificate
  • Examination: Practical project work with final presentations
  • Teaching Times: Full-time
    Monday to Friday from 8:30 a.m. to 3:35 p.m. (in weeks with public holidays from 8:30 a.m. to 5:10 p.m.)
  • Language of Instruction: German
  • Duration: 12 Weeks

Programming with Python

Python basics (approx. 1 day)

History, concepts

Usage and areas of application

syntax


First steps with Python (approx. 5 days)

Numbers

Strings

Date and time

Standard input and output

list, tuple dict, set

Branches and loops (if, for, while)


Artificial intelligence (AI) in the work process

Presentation of specific AI technologies

and possible applications in the professional environment


Functions (approx. 5 days)

Define your own functions

Variables

Parameters, recursion

Functional programming


Troubleshooting (approx. 0.5 days)

try, except

Intercept program interruptions


Object-oriented programming (approx. 4.5 days)

Python classes

Methods

Immutable objects

Data class

Inheritance


Graphical user interface (approx. 1 day)

Buttons and text fields

Grid layout

File selection


Project work (approx. 3 days)

To consolidate the content learned

Presentation of the project results

Relational databases with SQL

Basics of database systems and SQL (approx. 3 days)

Overview of database systems and models

Redundant data and data integrity

Normalization and BCNF

Database design and entity relationship model (ERM)

Primary and foreign keys

Relationships between relations

Data types in SQL

Indexes and performance

Constraints and validation

Queries (SQL)

Forms and reports in modern DBMS

Circular reference and dependency management


Introduction to SQL Server Management Studio (SSMS) (approx. 2 days)

Overview of SQL Server and SSMS

Physical database design

Creating tables and defining data types

Constraints, default values and relationships

Database diagrams and relationships

Backup and restore


Artificial intelligence (AI) in the work process

Presentation of specific AI technologies

and possible applications in the professional environment


Introduction to DDL (Data Definition Language) (approx. 8 days)

SQL basics and advanced syntax

Creating tables and defining constraints

Operators and function definitions

Queries and manipulation of data

Error handling and transaction management


DCL - Data Control Language and Security (approx. 1 day)

User administration and authorizations

Roles, authorizations and auditing


Data types, data import and export in modern systems (approx. 1 day)

Data import and export

Modern data types


Project work (approx. 5 days)

To consolidate the content learned

Presentation of the project results

Data analytics

Introduction to data analysis (approx. 1 day)

CRISP-DM reference model

Data analytics workflows

Definition of artificial intelligence, machine learning, deep learning

Requirements and role in the company of data engineers, data scientists and data analysts


Review of Python basics (approx. 1 day)

data types

Functions


Data analysis (approx. 3 days)

Central Python modules in the context of data analytics (NumPy, Pandas)

Process of data preparation

Data mining algorithms in Python


Artificial intelligence (AI) in the work process

Presentation of specific AI technologies

and possible applications in the professional environment


Data visualization (approx. 3 days)

Explorative data analysis

insights

Data quality

Benefit analysis

Visualization with Python: Matplotlib, Seaborn, Plotly Express

Data storytelling


Data management (approx. 2 days)

Big data architectures

Relational databases with SQL

Comparison of SQL and NoSQL databases

Business Intelligence

Data protection in the context of data analysis


Data analysis in a big data context (approx. 1 day)

MapReduce approach

Spark

NoSQL


Dashboards (approx. 3 days)

Library: Dash

Structure of dashboards - Dash components

Customizing dashboards

Callbacks


Text Mining (approx. 1 day)

Data preprocessing

Visualization

Library: SpaCy


Project work (approx. 5 days)

To consolidate the content learned

Presentation of the project results



Changes are possible. The course content is updated regularly.

After the course, you will have a compact, basic knowledge of programming with Python. You will be able to use the programming language with its classes, libraries and functions with confidence.

After the course, you will also be able to set up and manage relational databases with SQL, create views and execute complex queries, including using SQL functions. The course is taught on the Microsoft SQL Server using the Microsoft SQL Server Management Studio.

Furthermore, you can analyse, visualize and manage data. You also understand the use of dashboards and text mining.

The course is aimed at people with a degree in computer science, business informatics, mathematics, business administration or comparable qualifications.

As companies have to manage and structure ever-increasing volumes of data to evaluate and set objectives for their business processes, data analysis skills are in demand in all sectors.

Your meaningful certificate provides a detailed insight into the qualifications you have acquired and improves your career prospects.

Didactic concept

Your lecturers are highly qualified both professionally and didactically and will teach you from the first to the last day (no self-study system).

You will learn in effective small groups. The courses usually consist of 6 to 25 participants. The general lessons are supplemented by numerous practical exercises in all course modules. The practice phase is an important part of the course, as it is during this time that you process what you have just learned and gain confidence and routine in its application. The final section of the course involves a project, a case study or a final exam.

 

Virtual classroom alfaview®

Lessons take place using modern alfaview® video technology - either from the comfort of your own home or at our premises at Bildungszentrum. The entire course can see each other face-to-face via alfaview®, communicate with each other in lip-sync voice quality and work on joint projects. Of course, you can also see and talk to your connected trainers live at any time and you will be taught by your lecturers in real time for the entire duration of the course. The lessons are not e-learning, but real live face-to-face lessons via video technology.

 

The courses at alfatraining are funded by Agentur für Arbeit and are certified in accordance with the AZAV approval regulation. When submitting a Bildungsgutscheinor Aktivierungs- und Vermittlungsgutschein, the entire course costs are usually covered by your funding body.
Funding is also possible via Europäischen Sozialfonds (ESF), Deutsche Rentenversicherung (DRV) or regional funding programs. As a regular soldier, you have the option of attending further training courses via Berufsförderungsdienst (BFD). Companies can also have their employees qualified via funding from Agentur für Arbeit (Qualifizierungschancengesetz).

We will gladly advise you free of charge. 0800 3456-500 Mon. - Fri. from 8 am to 5 pm
free of charge from all German networks.
Contact
We will gladly advise you free of charge. 0800 3456-500 Mon. - Fri. from 8 am to 5 pm free of charge from all German networks.