"Python is the new Excel - essential skills for Banking & Data Analysis" - The Python Data Analytics training course will help you become fluent in the use of the Python programming language, with the purpose of automating tasks such as acquisition, cleaning and analysis of digital data.
Using interactive examples and hands-on exercises, the course covers the core concepts of Python programming, which provides participants with the foundations to achieve a high degree of independence and flexibility for their analysis process. It then continues with a focus on how Python tools and libraries like Pandas can help the audience performing data wrangling and data analysis effectively.
• The Anaconda distribution as Python Data Science platform
• Overview on Python virtual environment set-up
• Running Python code in Jupyter notebook
• Built-in data types in Python
• Working with strings, numbers, lists, tuples and dictionaries
• Control flow statements
• Conditional execution with if statements
• Conditional loops with where statements
• Looping over a sequence with for statements
• Defining and using custom functions
• Working with dates and times
• Accessing data on file (CSV, JSON, ...)
• Working with data in pandas
• Retrieving data in pandas
• Data manipulation in pandas
• Handling missing data in pandas
• Data Analysis in pandas
• Data Visualisation in pandas
• Working with multiple tables
• Time Series with pandas
• Working with text data in DataFrames
• SQL databases
• Data Visualisation with matplotlib and plotly
Quants, Data Scientists, Data Analysts, Financial Analysts, Researchers, Business Intelligence experts and Developers who are new to Python.
Software developers who are new to Python and Data Science or want to know more about the Python tools for Data Analysis.
"I hadn't integrated Pandas with Python before joining my company. So it's very useful to consolidate my understanding of such skill via this course. The Jupyter notebooks provided will be a valuable resource for revising the materials and are really well laid out."
JL, Data Analyst, Python for Data Analytics, March 2021
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