When does class start/end?
Class hours may vary, please reach out to contact@ascendientlearning.com if you have any questions.
Essential NumPy and Pandas for Data Science
Apply NumPy and Pandas to daily data work with production-grade efficiency. NumPy work covers matrix math, vectorized broadcast operations, array fundamentals, and the efficiency patterns that...
Read More
$1,665USD
Duration
2 days
Course Code
DS-1101
Available Formats
Classroom
Overview
Course Description
Apply NumPy and Pandas to daily data work with production-grade efficiency. NumPy work covers matrix math, vectorized broadcast operations, array fundamentals, and the efficiency patterns that distinguish production from prototype code: preallocation, profiling, and big-data techniques. Pandas work covers Series, DataFrames, I/O across multiple file types with Dask for big data, descriptive statistics, manipulation patterns, memory optimization, missing-data handling, GroupBy, and profiling. Hands-on labs produce a body-measurement comparison, a cleaned housing dataset, a Dask big-data analysis, and a DataFrame-optimization benchmark that quantifies the speedup against naive Python. The course is designed for data scientists, analysts, and software developers who already use Python and want their NumPy and Pandas to run at production efficiency.
Skills Gained
By the end of this course, participants will be able to:
- Apply standard data-science libraries to increase code reuse and portability
- Clean preprocessed data to uncover actionable insights
- Visualize data effectively for strategic decisions
- Optimize NumPy code to enhance pipeline performance
- Build the data-handling foundations needed for predictive AI
Who Can Benefit
This course is designed for:
- Data Scientists & Analysts
- Software Developers
Prerequisites
Participants should enter this course with:
- Practical Python Experience
Organizational Objectives
This course assists organizations to:
- Reduce data-pipeline cost through NumPy vectorization and Pandas memory optimization
- Lower data-quality risk through codified validation and missing-data handling
- Build a working NumPy and Pandas discipline across data-science teams
- Establish reusable I/O and DataFrame patterns that compound across projects
Software
All attendees must have a modern web browser and an Internet connection.
Course Details
Course Details
Module 1 - Fundamentals of NumPy
By the end of this module, you will be able to articulate why NumPy is central to data science, perform efficient matrix math through vectorized broadcast operations, work with NumPy array basics, and use NumPy as a foundation for model-building.
- Why learn NumPy and how it relates to C and pure Python
- Efficient matrix math
- Vectorized (broadcast) operations
- NumPy array basics
- Basic array operations
- Using NumPy for model-building
- Hands-on Lab: Practice NumPy array operations on real body-measurement data with deliberate vectorization patterns.
Module 2 - Efficient Use of NumPy
By the end of this module, you will be able to apply NumPy best practices for efficiency, manipulate existing arrays without unnecessary copies, preallocate and replace, profile and optimize computations, and apply best practices for big-data NumPy work.
- NumPy Best Practices for Efficiency
- Mangling Existing Arrays
- Vectorized (Broadcast) Operations Examples
- Preallocation and Replacement
- Profiling and Optimization Techniques
- NumPy Best Practices for Big Data
- Hands-on Lab: Apply broadcasting and preallocation through an optimization-game exercise that quantifies the speedup against naive code.
Module 3 - Fundamentals of Pandas
By the end of this module, you will be able to use Pandas Series and DataFrames to manipulate tabular data, recognize the relationship between NumPy and Pandas, validate data quality, and manage indexes.
- Pandas use cases and its relationship to NumPy
- Pandas Series
- DataFrames
- Key parts of a DataFrame and Series
- Data quality validation
- Managing the index
- Hands-on Lab: Inspect and clean a real-world housing dataset using Pandas.
Module 4 - Pandas I/O and Descriptive Statistics
By the end of this module, you will be able to read and write data across multiple file types, optimize memory usage during I/O, compute basic descriptive statistics with Pandas, and process big-data workflows using Dask.
- Data I/O with Different File Types
- Efficient Reading and Writing with Pandas
- Optimizing Memory Usage During Data I/O
- Basic Descriptive Statistics
- Big Data with Pandas
- Hands-on Lab: Practice with multiple file types and run a Dask analysis on a data corpus too large for in-memory Pandas.
Module 5 - Data Manipulation with Pandas
By the end of this module, you will be able to explore data, access specific rows and columns, produce basic visualizations, choose appropriate chart types, and use Matplotlib and Seaborn for publication-quality output.
- Data Exploration Basics
- Accessing Specific Rows and Columns
- Data Visualization
- Basic Chart Types and Interpretation
- Matplotlib Basics
- Seaborn for Beautiful Graphs
- Hands-on Lab: Explore real-world data with Pandas and produce visualizations that surface the most insightful relationships.
Module 6 - Efficient DataFrame Operations
By the end of this module, you will be able to apply Pandas DataFrame best practices, choose between Pandas, NumPy, and base Python objects for performance, handle missing data, perform aggregation with GroupBy, and profile DataFrame operations.
- Best Practice for Pandas DataFrames
- Optimizing Pandas, NumPy, Base Python Objects
- Preallocation for DataFrames
- Handling Missing Data
- Aggregation and GroupBy Operations
- Profiling and Performance Optimization
- Hands-on Lab: Run an optimization-game session on a DataFrame workflow and profile the result.
Schedule
FAQ
Does the course schedule include a Lunchbreak?
Classes typically include a 1-hour lunch break around midday. However, the exact break times and duration can vary depending on the specific class. Your instructor will provide detailed information at the start of the course.
What languages are used to deliver training?
Most courses are conducted in English, unless otherwise specified. Some courses will have the word "FRENCH" marked in red beside the scheduled date(s) indicating the language of instruction.
What does GTR stand for?
GTR stands for Guaranteed to Run; if you see a course with this status, it means this event is confirmed to run. View our GTR page to see our full list of Guaranteed to Run courses.
How do I find an Ascendient Learning training location?
We have training locations across the United States and Canada - View a complete list of classroom training locations.
Which delivery formats are available?
At Ascendient Learning, we offer training that is Instructor-Led, Online, Virtual, and Self-Paced.
Does Ascendient Learning deliver group training?
Yes, we provide training for groups, individuals and private on sites. View our group training page for more information.
What does vendor-authorized training mean?
As a vendor-authorized training partner, we offer a curriculum that our partners have vetted. We use the same course materials and facilitate the same labs as our vendor-delivered training. These courses are considered the gold standard and, as such, are priced accordingly.
Is the training too basic, or will you go deep into technology?
It depends on your requirements, your role in your company, and your depth of knowledge. The good news about many of our learning paths, you can start from the fundamentals to highly specialized training.
How up-to-date are your courses and support materials?
We continuously work with our vendors to evaluate and refresh course material to reflect the latest training courses and best practices.
Are your instructors seasoned trainers who have deep knowledge of the training topic?
Ascendient Learning instructors have an average of 27 years of practical IT experience and have also served as consultants for an average of 15 years. To stay current, instructors spend at least 25 percent of their time learning new, emerging technologies and courses.
Do you provide hands-on training and exercises in an actual lab environment?
Lab access is dependent on the vendor and the type of training you sign up for. However, many of our top vendors will provide lab access to students to test and practice. The course description will specify lab access.
Will you customize the training for our company’s specific needs and goals?
We will work with you to identify training needs and areas of growth. We offer a variety of training methods, such as private group training, on-site of your choice, and virtually. We provide courses and certifications that are aligned with your business goals.
How do I get started with certification?
Getting started on a certification pathway depends on your goals and the vendor you choose to get certified in. Many vendors offer entry-level IT certification to advanced IT certification that can boost your career. To get access to certification vouchers and discounts, please contact info@ascendientlearning.com.
Will I get access to content after I complete a course?
You will get access to the PDF of course books and guides, but access to the recording and slides will depend on the vendor and type of training you receive.
How do I request a W9 for Ascendient Learning?
View our filing status and how to request a W9.
Reviews
The class was very vast paced however the teacher was very good at checking in on us while giving us time to complete the labs.
Very interactive and in-depth course that really got me ready for the industry
Easy to work with. Learning material pdfs were able to be printed out in color which was very nice to write on.
Course was great and informative. The instructor had a good flow and was very personable.
Thorough explanations by the instructor along guide and practical training sim of software.
