Instantly analyze large volumes of data
To have universal knowledge that can be applied in any field
Who is Data Analyst
and what is python for data science?
The Data analyst is a person who conducts a series of statistical analyzes with the aim of solving business problems that have not yet found a solution. He works with various analysis tools and at the same time with ready-made analytical solutions. He knows several programming languages and formalize various assumptions. This course in Baku will not only teach you all the knowledge that Data Analyst needs, at the same time it will show you how to think abstract, to see the hidden data behind various indicators, and uncover the connections between the data. All these tasks are carried out via python. The acquired skills will significantly support overcoming difficult tasks. You will be able to deeply review different hypotheses and choose the most effective and appropriate means for their verification.
Data Analyst – is a specialist who makes various analyzes on this data because of data processing, builds different strategies, gives new plans and recommendations.
What you will learn in this course of python for data science in Azerbaijan
You will not be faced with innovations during course of python for data science: individual consultations by the mentor during the study period, professional support in all developed projects, working experience with the team leader during teamwork.
- What is analytical thinking?
- Introduction to Google charts
- Google charts with details
- Basics of Statistics
- Source of Data
- Data visualization with details
- Python as a Data Analysis tool
- Basics of Python and Kit
- Basic data types and periods
- Functions and classes
- Advanced data types: array, sets, dictionaries
- Python for Data Analysis tool: numpy and scipy
- Python for Data Analysis tool: pandas
- Basic libraries to connect from Python to DB
- Matplotlib, seaborn visualization tools
- Choosing a visual method for the task
- Basics of SQL
- SQL with details
- Writing optimized applications
- No SQL
- Numpy library. Calculation tasks
- Pandas library
- Functions and data processing
- Pandas with details
- Complex calculation fields, overview of key function groups
- Matplotilib & Seaborn library. Data visualization
- Basics of descriptive statistics, types of distribution in Python
- Central limit Theorem and statistical data analysis in Python
- Basic statistical and hypothesis tests