Data Wrangling with Python
Use the Power of Python to Clean, Transform, and Scale Data Workflows
In today’s fast-paced, data-driven marketplace, the ability to clean, transform, and integrate raw data is no longer optional—it’s business-critical.
Data Wrangling with Python provides a practical, hands-on approach to preparing data for immediate insights and advanced analytics, using industry-standard tools like Pandas, NumPy and Jupyter Notebooks. Through real-world exercises, you’ll learn to handle everything from messy CSV files to semi-structured JSON data, identify data quality issues, and create streamlined workflows.
This course equips you with essential, in-demand skills that not only save time and reduce errors but also position you—and your organization—for ongoing success in AI and machine learning initiatives.
The urgency to master these skills has never been greater as organizations race to harness data-driven decision-making for competitive advantage.
Prerequisite: Basic python coding skills:
- Basic Python syntax
- Flow control structures (loops and conditionals)
- Function definition and calling
- Basic Python data structures (lists and dictionaries)
What You’ll Learn from the Data Wrangling with Python Course
Streamline Data Loading and Ingestion
- Read and write files easily with Python and its libraries
- Ingest data in CSV, JSON, and Excel files into pandas DataFrames
- Export data in common formats for use in other analysis tools
Clean, Organize and Automate Data Workflow
- Identify and resolve missing values and duplicates across diverse datasets
- Sort, group, and aggregate data to understand differences between segments
- Merge data from different sources together
- Handle missing data easily and elegantly
- Automate transformations with Python to eliminate repetitive spreadsheet tasks
Communicate Effectively with Visuals
- Get faster insights by using appropriate visualization techniques
- Communicate the results of your analysis with impactful graphics
Gain Insights from Data Analysis
- Utilize Jupyter Notebooks for interactive coding, rapid prototyping, and clear documentation
- Discover trends by analyzing time series data
- Determine the significance of results with confidence intervals
- Distinguish successes from failures with statistically rigorous hypothesis testing
Foundation for AI & Machine Learning
- Assemble clean data sets ready to be fed into advanced analytics and predictive models
- Automate data transformations for input to machine learning models
- Build the in-demand skills in programming and statistics for data driven innovation and insights
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Self-Paced, Hybrid Course
- 21—30 hours course (depends on experience with Python and data)
- 9 hours of self-paced content
- 4—6 hours exercises
- 8—15 hours mini-project
- Hands-on, project oriented experiential learning
- Learn at your own pace
- Instructor office hours for supplemental support
- No travel
Common Roles
- Junior business analysts, data analysts, finance analysts, BI analysts, MI analysts, product operations, design operations, project managers
- Individuals who want to go beyond the basics of Python, and learn how to prepare the data for analysis and perform simple analysis techniques to secure insights
Key Takeaways
By the end of this course, you will be able to:
Accelerate Data Operations
- Automate time-consuming tasks (e.g., data ingestion, cleaning) to improve overall workflow speed and consistency
Enhance Data Quality & Reliability
- Learn to use tools to confidently detect and correct errors or inconsistencies in datasets, reducing risk in downstream analytics
Deliver Immediate Business Impact
- Transform raw data into actionable insights faster, giving your organization a competitive edge in real-time decision-making
- Communicate findings effectively to stakeholders, bridging the gap between technical data preparation and strategic outcomes
Prepare for Advanced Analytics
- Take on more complex analytical projects with confidence, knowing your data foundation is strong.
Ready to start?
Data Wrangling with Python
After completing Data Wrangling with Python, you’ll be equipped to confidently tackle messy, disparate datasets, rapidly convert them into valuable business insights, and lay the groundwork for scalable AI and machine learning endeavors.
Your Path To Certification
- Enroll in All Three Courses: Complete Data Wrangling with Python, AI & Machine Learning, and Generative AI for NLP.
- Engage & Apply: Learn at your own pace, apply concepts with hands-on exercises, and attend office hours for personalized support.
- Demonstrate Mastery: Validate your new abilities through real-world mini-projects.
- Earn the Credential: Upon successful completion of all three courses, you’ll be awarded the Data Science Analyst Certification.
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