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This three day course is aimed at those wishing to learn how to use Python to work with and handle Data. When combined with our Introduction to Data Science course you would be set up well to follow a Python learning journey into Data Science, Machine Learning, and Artificial Intelligence.

During the programme you will be introduced to Python and specific development environments and packages for working with Data, with a focus on NumPy, Pandas, Matplotlib, and Seaborn.

Along the way you will see how to clean and manipulate tabular data, apply simple statistical techniques and data visualisations, and learn about how to control the flow of your program in order to automate processes.

Throughout the course you will engage with activities and discussions with one of our Data Science technical specialists and complete technical lab activities to practice the techniques you have learnt and develop ideas for further practice.

No prior experience with Python is necessary, though it is assumed that you will be familiar with core data concepts such as simple table structures and data types – all the pre-requisites you need are covered by our Data Fundamentals course.

To apply your knowledge of data practically using Python for handling data in roles that involve data analysis, data engineering, data science, machine learning and AI, and Data related Ops roles.
If you are in a Software or IT related role where you work with Python, this course will support you in learning how to work with Data.
To ensure you have the necessary pre-requisite knowledge when combined with Introduction to Data Science should you wish to progress onto Data Science and Machine Learning with Python.

1. Introduction to Programming for Data Handling

Describe the pros and cons of using programming languages to work with data
Identify the languages most suitable for data handling
Explain the challenges of using programming languages versus data analysis tools

2. Introduction to Python and IDEs

Describe the key attributes of the Python programming language.
Explain the role of the Jupyter IDE for Python programming.
Use the Jupyter IDE to write a basic Python program.
Write a program which uses string, integer, float and boolean data types.

3. Data Structures, Flow Control, Functions, and Basic Types

Construct collections to solve data problems.
Utilise selection and iteration syntax to control the flow of a Python program.
Write reusable functions which can be used to alter data & automate repetitive tasks.
Use Python's built-in open function to create, read, and edit files.

4. Mathematical and Statistical Programming with NumPy

Describe the core features of NumPy arrays.
Create, index, and manipulate NumPy arrays to solve data problems.
Use masking and querying syntax to retrieve desired values.
Use vectorised ufuncs.

5. Introduction to Pandas

Create, manipulate, and alter Series and DataFrames with Pandas.
Define and change the indices of Series & Dataframes.
Use Pandas' functions and methods to change column types, compute summary statistics and aggregate data.
Read, manipulate, and write data from csv, xlsx, json and other structured file formats.

6. Data Cleaning with Pandas

Identify missing data and apply techniques to deal with it.
Deduplicate, transform and replace values.
Use DataFrame string methods to manipulate text data.
Write regular expressions which munge text data.

7. Data Manipulation with Pandas

Construct Pivot tables in Pandas.
Time series manipulation.
Stream data into Pandas to handle data size problems.

8. Methods for Visualising Data

Construct and tailor basic data visualisations using Matplotlib & Seaborn for both numeric & non-numeric data.
Meaningfully visualise aggregate data using Matplotlib and Seaborn.

Data Handling in Python Training Course in Germany

The Federal Republic of Germany is the second most populous country in Europe and is located in Central Europe. The official language of the country is German. Germany is one of the richest countries in the world. The main exports of the country include motor vehicles and iron and steel products.

Here are some fun facts about Germany:
The fairy tale writer, the Brothers Grimm, came from Germany and wrote many famous stories such as Cinderella, Snow White, and Sleeping Beauty.
Germany is home to the largest theme park in Europe, the Europa-Park.
The famous composer Ludwig van Beethoven was born in Germany.
The Autobahn, the German highway system, is known for having no general speed limit.

Berlin was divided by the Berlin Wall from 1961 to 1989. Known for its street art, Berlin has many colorful murals and graffiti throughout the city. Also, Berlin is home to many famous museums, such as the Pergamon Museum and the Museum Island. Many clubs and bars stay open until the early hours of the morning in this big city.

Another popular city is Munich, which is famous for its Oktoberfest beer festival that attracts millions of visitors every year. Munich is also home to many historic buildings, including Nymphenburg Palace and the Marienplatz town square.

The country's capital and largest city is Berlin, however Frankfurt is considered to be the business and financial center of Germany. It is home to the Frankfurt Stock Exchange, the European Central Bank, and many other financial institutions. Because of its central location within Europe and its status as a major financial hub, Frankfurt is often referred to as the "Mainhattan," a play on the city's name and its association with the Manhattan financial district in New York City.

Frankfurt is also a major transportation hub, with the largest airport in Germany and one of the largest in Europe, Frankfurt Airport. Additionally, it is a popular destination for tourists, with its historic city center, beautiful parks, and vibrant cultural scene.

Some of the top German technology companies like Siemens AG, Bosch, SAP SE, Deutsche Telekom, Daimler AG and Volkswagen has business centers in Frankfurt. The country has a strong tradition of engineering and innovation, and is home to many other world-class technology companies and research institutions.

Tailored to meet the specific needs of Germany, Bilginç IT Academy combines cutting-edge training methodologies with our comprehensive range of Certification Exam preparation courses and accredited corporate training programs. Experience a transformative approach to IT training that will redefine your expectations.

Data Handling in Python Training in Germany

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Data Handling in Python Training in Germany

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