Python for Data Science Course

Name: Python for Data Science
Price: 1795.00 USD
Availability: InStock
Rating: 4.5 (1200 reviews)

Price
$1,795.00 USD

Duration
3 Days

Delivery Methods
Virtual Instructor Led
Private Group

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Python for Data Science Course Overview

Did you know that data professionals spend up to 80% of their time cleaning and preparing data? Python is the industry’s go-to language for streamlining this process, making it an essential tool for anyone looking to analyze, visualize, and derive insights from data.

Master the complete data science tech stack essential for landing a job at the world’s leading companies. This Python for Data Science course takes a structured, in-depth approach, helping you not only learn how to apply data science but also why it matters. Through a carefully balanced mix of real-world case studies and the mathematical theory behind key data science algorithms, you'll develop both the practical skills and foundational understanding needed to excel in the field.

Please note, this course is able to be offered in either 3 full day sessions or 5 evening sessions. See the schedule below.

What Is Included

Expert Instruction – Learn from industry professionals with real-world experience in data science.
6-Month Access to On-Demand Videos – Reinforce your learning with exclusive reference videos
Guaranteed to Run – No last-minute cancellations! Your course is guaranteed to take place, so you can plan with confidence.
Flexible Rescheduling – Need to change your course date? Rescheduling options are available (see conditions).
FREE Course Retake – Reinforce your skills by retaking the course at no additional cost (see conditions).
Develop Real-World Data Science Projects – Apply your skills to hands-on projects using Jupyter Notebook and real-world datasets.

Course Objectives

The Python for Data Science course teaches the fundamentals of Python for data analysis and visualization. Participants will work with key libraries like Pandas, NumPy, Matplotlib, and Seaborn to clean, transform, and analyze data. They will create interactive visualizations to communicate insights effectively and apply their skills through hands-on projects using Jupyter Notebook and real-world datasets.

Who Should Attend?

Intermediate Python developers looking to use Python to explore and visualize large or complex data sets. Check out our Introduction to Python course if you’re new to Python.

Top-rated instructors: Our crew of subject matter experts have an average instructor rating of 4.8 out of 5 across thousands of reviews.
Authorized content: We maintain more than 35 Authorized Training Partnerships with the top players in tech, ensuring your course materials contain the most relevant and up-to date information.
Interactive classroom participation: Our virtual training includes live lectures, demonstrations and virtual labs that allow you to participate in discussions with your instructor and fellow classmates to get real-time feedback.
Post Class Resources: Review your class content, catch up on any material you may have missed or perfect your new skills with access to resources after your course is complete.
Private Group Training: Let our world-class instructors deliver exclusive training courses just for your employees. Our private group training is designed to promote your team’s shared growth and skill development.
Tailored Training Solutions: Our subject matter experts can customize the class to specifically address the unique goals of your team.

What Is Python for Data Science?

Python for Data Science is a specialized course that teaches you how to use Python for data analysis, visualization, machine learning, and statistical modeling. It covers essential tools like Pandas, NumPy, Matplotlib, Seaborn, and Scikit-learn.

How Much Can I Make with Python for Data Science Skills?

Salaries vary based on experience, location, and specialization. Here are median annual salaries for common data-related roles (source: U.S. Bureau of Labor Statistics & Glassdoor):

Data Analyst – $70,000
Data Scientist – $120,000
Machine Learning Engineer – $130,000
Business Intelligence Analyst – $87,000

What Is Covered in This Course?

This course includes:

Python Basics – Variables, data types, loops, functions
Data Handling with Pandas – Importing, cleaning, and transforming data
Numerical Computing with NumPy – Working with arrays and mathematical operations
Data Visualization – Creating graphs with Matplotlib and Seaborn
Machine Learning Basics – Introduction to Scikit-learn for predictive modeling
Real-World Data Projects – Hands-on projects with real datasets

What Jobs Can I Get with Python for Data Science Skills?

With Python for Data Science expertise, you can qualify for roles such as:

Data Analyst
Data Scientist
Machine Learning Engineer
Business Intelligence Analyst
Research Analyst

Why Should I Learn Python for Data Science?

Python is the leading programming language for data science due to:
✅ Ease of Learning – Beginner-friendly syntax
✅ Powerful Libraries – Extensive tools for data analysis and machine learning
✅ High Demand – Python is used by major companies like Google, Amazon, and Netflix
✅ Career Growth – Opens doors to advanced data science and AI roles

Is Python for Data Science Worth It?

Absolutely! Python for Data Science is one of the most in-demand skills in today’s job market. Learning Python can help you break into data-related careers, increase your earning potential, and work on exciting real-world projects.

Learning Credits: Learning Credits can be purchased well in advance of your training date to avoid having to commit to specific courses or dates. Learning Credits allow you to secure your training budget for an entire year while eliminating the administrative headache of paying for individual classes. They can also be redeemed for a full year from the date of purchase. If you have previously purchased a Learning Credit agreement with New Horizons, you may use a portion of your agreement to pay for this class.

If you have questions about Learning Credits, please contact your Account Manager.

Course Prerequisites

To be successful in this course, learners should have the level of knowledge and experience gained from Introduction to Python

Python for Data Science Agenda

1. Introduction to Python for Data Science

Overview of Python and its role in data science
Setting up Python environments (Anaconda, Jupyter Notebooks)
Writing and running Python scripts

2. Working with Jupyter Notebooks

Introduction to Jupyter Notebooks
Markdown and code cells
Running, saving, and sharing notebooks

3. Numerical Computing with NumPy

Understanding arrays and their advantages
Creating and manipulating NumPy arrays
Mathematical operations and broadcasting

4. Data Manipulation with Pandas

Understanding Series and DataFrames
Importing and exploring datasets
Filtering, sorting, and transforming data

5. Data Input and Output (I/O)

Reading and writing Excel files
Working with CSV files
Connecting and querying SQL databases

6. Converting Datasets to Pandas DataFrames

Transforming structured and unstructured data
Importing datasets from APIs and web sources

7. Advanced Data Handling

Altering specific data using custom functions
Handling missing data – filling, dropping, and imputing values
Aggregating data using group operations

8. Data Visualization with Matplotlib

Creating fully customizable plots
Implementing custom figures and axis
Adding labels, legends, and annotations

9. Statistical Data Visualization with Seaborn

Creating scatter plots
Generating distribution plots
Visualizing summary statistics with box plots

10. Hands-on Projects and Real-World Applications

Data analysis case studies
End-to-end data science project
Best practices for working with large datasets