Python, renowned for its simplicity and robustness, has become an indispensable language in various fields, including data science, machine learning, and business analytics. Its extensive libraries for data manipulation and analysis make Python a go-to tool for individuals and organizations aiming to derive meaningful insights from data. Geared for technical users new to Python, Hands-On Practical Python for Data Wrangling & Transformation is a four-day, comprehensive hands-on course that will provide you with the hands-on practice and foundational skills needed to navigate Python programming and data wrangling effectively.Throughout the course you’ll explore critical topics such as leveraging Python’s built-in types, structuring and organizing code, manipulating file code, and deep-diving into data wrangling. You will also gain exposure to advanced topics, including SQL and RDBMS, and their integration with Python for efficient data handling and management. The focus remains firmly on delivering practical skills that can be directly applied in a professional setting.Our hands-on approach sets this course apart. A significant portion of the learning experience will be dedicated to practical lab exercises where you will apply Python, along with tools like NumPy, Pandas, Matplotlib, SQLite, and SQLAlchemy, to real-world data scenarios. These labs aim to simulate real job tasks, from data transformation to web scraping, preparing you to handle similar tasks in your current or future roles. The course also includes a few bonus, time-permitting chapters on applying Generative AI / AI / GPT to Python and Data Wrangling.The course leverages our innovative Learning Experience Platform, promoting an interactive and collaborative learning environment, under the real-time live guidance of our industry expert. Upon course completion, you will have a strong foundation in Python programming and data wrangling, be capable of handling files and databases efficiently, and possess the skills to extract meaningful insights from complex datasets, directly benefiting your professional endeavors.
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Please contact us at info@toptalentlearning.com or 469-721-6100 for this course schedule. |
Course Topics / Agenda
Please note that this list of topics is based on our standard course offering, evolved from typical industry uses and trends. We can work with you to tune this course and level of coverage to target the skills you need most. Course agenda, topics and labs are subject to adjust during live delivery in response to student skill level, interests and participation.
1. Introduction to Python
· Understand Python’s significance and its application in modern enterprises.
· Python Basics and Syntax
· Python Built-in Types
· Variables, Lists, Dictionaries, and Tuples • Control Structures: If, For, While
· Lab: Hands-on Python basics using Python, Jupyter Notebook
2. Organizing and Structuring Code
· Gain skills to write efficient and organized Python code.
· Writing Functions and Classes
· Modules and Packages
· Error Handling and Exceptions • Pythonic Coding Practices
· Lab: Code organization and modularization
3. Manipulating Files
· Learn file handling in Python for reading and writing data
· Reading and Writing Text Files
· File Operations and Manipulation
· Working with JSON and CSV Files
· Directory Operations
· Lab: File operations and data extraction
4. Introduction to Data Wrangling with Python
· Grasp the concept of Data Wrangling and its importance in Python.
· Introduction to Data Wrangling
· Loading and Viewing Data
· Data Cleaning Techniques
· Data Transformation
· Lab: Initial data wrangling exercises
5. Deep Dive into NumPy, Pandas, and Matplotlib
· Discover essential Python libraries for data analysis and visualization.
· Introduction to NumPy
· Introduction to Pandas • Introduction to Matplotlib
· Data Analysis and Visualization Using Above Libraries
· Lab: Data manipulation and visualization tasks using Pandas, NumPy, Matplotlib
6. Advanced Data Wrangling with Python
· Gain advanced skills for wrangling data using Python.
· Merging and Joining DataFrames
· Handling Missing Data
· Date and Time Data
· String Manipulations
· Lab: Advanced data wrangling tasks using Python and Pandas
7. Web Scraping and Data Gathering
· Learn the techniques to extract data from the web.
· Introduction to Web Scraping • Using BeautifulSoup
· Regular Expressions in Python • APIs and JSON
· Lab: Web scraping tasks
8. Introduction to SQL and RDBMS
· Understand SQL’s role in data wrangling and Python’s integration with it.
· SQL Basics
· Python’s sqlite3 module
· SQL vs. NoSQL
· Using SQLAlchemy with Python
· Lab: Database interactions and data extraction tasks
9. Real-world Data Wrangling
· Apply learned skills to real-world data wrangling scenarios.
· Case Studies in Data Wrangling
· Best Practices in Data Wrangling
· Dealing with Large Datasets
· Building a Data Wrangling Pipeline
· Lab: Real-world data wrangling task
10. Next Steps in Python and Data Wrangling
· Overview of Advanced Python Topics
· Overview of Machine Learning with Python
· Overview of Big Data Tools (e.g., Spark)
· Lab: Exploring Machine Learning and Big Data Tools: Use Scikit-learn to create a basic Machine Learning model and then apply PySpark to handle a small simulated Big Data task.
11. Capstone Projects / Optional
· Lab Project: Hands-on Real-world Data Wrangling Project – Apply the skills learned throughout the course in a practical project.
· Project 1: Building a Data Pipeline – Extract, transform, and load data from multiple sources.
· Project 2: Web Scraping and Data Analysis – Extract data from the web and perform analysis.
Addendum: Post-Training Skills Development
· Continued Learning Resources
· Suggestions for Practical Applications of Skills Learned
· Recommended Python and Data Science Communities and Forums
· Additional Tools for Data Science (e.g., Scikit-Learn, TensorFlow, PyTorch, etc.)
· Contributing to Open-Source Projects
Bonus Chapters: (Optional / Time Permitting)
12. Bonus: Generative AI for Python Programming and Data Wrangling
· Understand the role of AI in code generation and its applications in Python and Data Wrangling.
· Introduction to Generative AI •
· Overview of GPT Technology
· GPT Applications in Python Programming and Data Wrangling
· Using AI for Code Completion, Error Detection, and Data Analysis
· Lab: Exploring AI-assisted Python programming and data wrangling with GPT technology
13. Bonus: Advanced Python Skills Using AI Technologies
· Enhance Python skills and productivity using AI-powered tools.
· Overview of AI Tools for Python
· AI for Automated Testing and Debugging
· Using AI for Code Optimization • Machine Learning-based Predictive Analytics with Python
Lab: Apply AI tools to improve Python programming and perform predictive analytics
This course is approximately 50% hands-on, combining expert lecture, real-world demonstrations and group discussions with machine-based practical labs and exercises. Our engaging instructors and mentors are highly experienced practitioners who bring years of current “on-the-job” experience into every classroom.
Working in a hands-on learning environment, guided by our expert team, attendees will learn to:
The ideal audience for this course are individuals in technical roles who have a basic understanding of data science and are looking to expand their skill set with Python programming and data wrangling. This may include data analysts, business intelligence professionals, junior data scientists, and IT professionals involved in data-focused roles. Additionally, researchers, academics, or other professionals seeking to streamline data analysis and management processes in their work might also find significant value in attending.
The ideal audience for this course are individuals in technical roles who have a basic understanding of data science and are looking to expand their skill set with Python programming and data wrangling. This may include data analysts, business intelligence professionals, junior data scientists, and IT professionals involved in data-focused roles. Additionally, researchers, academics, or other professionals seeking to streamline data analysis and management processes in their work might also find significant value in attending.