Python for Data Analyst
Lecture 1: Building Solid Python Programming Fundamental (Part 1)
- Understanding common Python use-cases in day to day working environment.
- Learning Python 2 and Python 3 differences, Python development environment (IDEs) and related software products.
- Introducing basic data types （string， numeric， boolean， list/tuple and dictionary）and how they are used in the real project.
Lecture 2: Building Solid Python Programming Fundamental (Part 2)
- Working with Python operators, conditional statements, loops and error handling.
- Writing your own functions
- Managing files with Python file I/O
- Brief introduction to Object Oriented Programming and real-world Classes use-cases
Lecture 3: Reading data with Python Pandas
- Pandas and Anaconda Introduction
- Reading CSV
- Reading Other delimited TXT files
- Reading Excel
- Reading JSON
- Reading HTML
- Reading Data Frames
- Reading other file types
Lecture 4: Processing data with Python Pandas
- Viewing and understanding your data
- Selecting and filtering data
- Cleaning and organizing data
- Grouping and summarizing data
- Joining and combining data from different sources
Lecture 5: Output data with Python Pandas
- Common Python Outputs in a typical business environment
- Writing to CSV
- Writing to Excel
- Writing to JSON
- Writing to other file formats
- Python visualization with Matplotlib
- Python statistical outputs (Business oriented, no prior stats knowledge required)
Lecture 6: Python with Databases and big data
- Introduction to Python with Database
- Live demo on how Python is used with other common software products including commonly used databases for Python (SQL Server, Postgres and MySQL, mongoDB)
- Understand the real Python eco-systems and current corporate big data and database strategies to find out the career opportunities for you.
Lecture 7: Cloud, Real-world Python projects, further studies and interview preparation
- Introduction to Python on the Cloud
- Understand the Python eco-systems on the cloud and current corporate big data and cloud strategies to find out the career opportunities for you.
- Brief introduction on several enterprise level Python projects
- Guidelines on directions of your future Python studies
- Common Python interview questions and how to prepare for them
- My ongoing supports for your learning journey
Yang Liu，多伦多数据分析专家，多大工商管理硕士（MBA），电脑硕士学士。15年数据架构师和分析师经验。从事美国，加拿大银行及医药行业。近10年教学经验，在银行、学校及教育机构有过多年 Python，SAS，R，VBA面向不同专业背景的学生教学经验。