Gain advanced skills to handle complex data sets, understand machine learning algorithms, and translate data into actionable insights

This course provides students with Python data science skills that can immediately be applied in real life. The course focuses on Pandas as the primary tool, using related packages such as NumPy and Seaborn to enhance processing and visualization.

Who Should Attend?

This course is designed for data professionals who already have foundational Python and Pandas skills and want to apply Python more effectively to real-world data analysis problems. Typical roles include data analysts, data scientists, engineers, and researchers.

We can organize this training at your preferred date and location. Contact Us!

Prerequisites

Participants should have a solid foundation in Python and introductory Pandas concepts. This course assumes prior experience with Python syntax, basic data structures, and simple data manipulation in Pandas.

What You Will Learn

Working in a hands-on, applied learning environment, participants will learn to:

Advanced Data Ingestion & Preparation: Efficiently import, clean, and export complex datasets using Pandas, preparing data for deeper analysis and reuse.
Sophisticated Data Selection & Indexing: Confidently navigate and subset data using advanced indexing techniques, Boolean logic, and multi-indexing for hierarchical datasets.
Data Aggregation & Summarization: Apply groupby() operations and aggregation functions to analyze trends, patterns, and summaries across large datasets.
Data Transformation & Reshaping: Transform, merge, and reshape datasets to support more effective analysis and streamlined analytical workflows.
Functional Data Processing: Apply user-defined and third-party functions to Pandas objects to extend analytical capabilities and customize data processing.
Advanced Data Visualization: Create clear, informative, and visually compelling data visualizations using advanced Matplotlib features and Seaborn enhancements.
NumPy for Analytical Efficiency: Utilize NumPy arrays and operations to manipulate large numerical datasets and improve analytical performance.
Applied Scientific Computing with SciPy: Gain practical exposure to key SciPy subpackages to support statistical analysis, optimization, and scientific workflows.

Training Outline

Pandas input and output
Reading data into Pandas dataframes and exporting to various formats.
- General input considerations
- Reading CSV Files
- Data cleaning
- Reading other data formats
- Exporting data
Pandas filtering and sorting
Selecting subsets of dataframes for focused analysis.
- Indexing rows and columns
- Multi-indexing
- Selection by conditions
- Sorting data
Pandas grouping and aggregation
Consolidating data and providing sums and other aggregate values.
- Using groupby()
- Aggregate functions
- Using data summaries
- Alternate approaches
Pandas Data Transformation
Manipulating datasets for simpler analysis.
- Applying functions to data
- Renaming columns and indexes
- Inserting and removing data
- Combining and merging dataframes
- Reshaping datasets
Advanced Matplotlib
Going beyond the basics with Matplotlib.
- Components of a figure
- Multiple plots
- Complex plots
- Matplotlib options and settings
- Customing styles (and everything else)
Seaborn
Learning how Seaborn supplements and improves on Matplotlib.
- What does Seaborn provide?
- Using themes
- Advanced plot types
- Fine-tuning the details
Using NumPy
Loading large datasets into NumPy arrays for further analysis.
- NumPy basics
- Creating arrays
- Indexing and slicing
- Builtin functions()
- Reading and writing data
Useful SciPy subpackages
A look at some of the 20-odd SciPy subpackages.
- What is SciPy?
- scipy.stats
- scipy.interpolate
- scipy.optimize

Why Choose Us

Experience live, interactive learning from the comfort of your home or office with Bilginç IT Academy's Online Instructor-Led Applied Python for Data Science (TTPS4876) Training. Engage directly with expert trainers in a virtual environment that mirrors the energy and schedule of a physical classroom.

Live Sessions: Join scheduled classes with a live instructor and other delegates in real-time.
Interactive Experience: Engage in group activities, hands-on labs, and direct Q&A sessions with your trainer and peers.
Global Expert Trainers: Learn from a handpicked global pool of expert trainers with deep industry experience.
Proven Expertise: Benefit from over 30 years of quality training experience, equipping you with lasting skills for success.
Scalable Delivery: Accessible worldwide with flexible scheduling to meet your professional needs through our globally available virtual classrooms.

Immerse yourself in our most sought-after learning style for Applied Python for Data Science (TTPS4876) Training. Our hand-picked classroom venues offer an invaluable human touch, providing a focused and interactive environment for professional growth.

Highly Experienced Trainers: Boost your skills with trainers boasting 10-20+ years of real-world experience.
State-of-the-Art Venues: Learn in high-standard facilities designed to ensure a comfortable and distraction-free experience.
Small Class Sizes: Our limited class sizes foster meaningful discussions and a personalized learning journey.
Best Value: Achieve your certification with high-quality training and competitive pricing.

Streamline your organization's training requirements with Bilginç IT Academy’s Onsite Applied Python for Data Science (TTPS4876) Training. Experience expert-led learning at your own business premises, tailored to your corporate goals.

Tailored Learning Experience: Customize the training content to fit your unique business projects or specific technical needs.
Maximize Training Budget: Eliminate travel and accommodation costs, focusing your entire budget on the training itself.
Team Building Opportunity: Enhance team bonding and collaboration through shared learning experiences in your workspace.
Progress Monitoring: Track and evaluate your employees' progression and performance with relative ease and direct oversight.

Why have you chosen us?

I have attended a training from Bilginc IT Academy before and I was satisfied.

I have attended a training from a different provider and it was not helpful.

Other

How many employees do you have in your IT department?

0 – 50

50 – 250

250 – 1000

1000+

Applied Python for Data Science (TTPS4876) Training

Who Should Attend?

Prerequisites

What You Will Learn

Training Outline

Why Choose Us

Online Instructor-Led Training (VILT)

Classroom Based Learning

Onsite / In-House Learning

Applied Python for Data Science (TTPS4876) Training Course Schedule