Course Code:
pythonanalyzeintegrate
Duration:
35 hours
Prerequisites:
- Basic programming knowledge
Audience
- Analysts
- Administrative staffs
- IT professionals
Overview:
Python is a high-level, general-purpose programming language known for its readability, simplicity, and versatility.
This instructor-led, live training (online or onsite) is aimed at beginner-level professionals who wish to develop essential Python programming skills for data analysis, process automation, and system integration.
By the end of this training, participants will be able to:
- Develop foundational and advanced skills in Python programming.
- Learn how to perform data analysis and visualization (dashboards).
- Automate repetitive tasks using Python scripting.
- Integrate Python with external platforms like Power BI, SQL, and Excel.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Course Outline:
Introduction to Python Programming
- Setting up the development environment (Jupyter Notebooks, IDEs)
- Python syntax, variables, and data types
- Control structures: Loops, conditionals, and functions
- Introduction to Python libraries: NumPy, Pandas, Matplotlib
Data Analysis and Visualization
- Data wrangling: Cleaning, filtering, and transforming data (using Pandas)
- Aggregating and summarizing data
- Data visualization: Line plots, bar graphs, pie charts, histograms (using Matplotlib and Seaborn)
- Dashboards with Plotly/Dash: Building dynamic dashboards
Process Automation with Python Scripts
- Automating tasks: File renaming, email automation, and web scraping
- Database integration: Connecting Python to SQL, MySQL, and SQLite
- Automating data extraction and updates with APIs (e.g., Google Sheets, REST APIs)
- Error handling: Best practices for reliable automation scripts
Advanced Data Integration and Analysis Tools
- Power BI integration: Using Python to analyze and feed data into Power BI
- Excel integration: Automating Excel tasks with openpyxl and pandas
- Introduction to ML with Python: Building basic classifiers using scikit-learn
- Creating data pipelines with ETL operations
Final Project and Practical Applications
- Group project: Developing a Python automation or visualization solution relevant to LNBR’s domain
- Code reviews and feedback sessions
- Certification exam and assessment
- Discussion on security best practices in Python applications
Summary and Next Steps