Python is a versatile programming language that's widely used in Data Science across various sectors of the economy. As a Data Science Professional, mastering Python can open up a range of career opportunities such as Software Engineer, Data Scientist, Coding Engineer, Software Developer, Engineering Manager, and Data Analyst.
Key Insights
- Python for Data Science is user-friendly and offers powerful functionalities.
- Python frameworks and libraries are ideal for mathematical functions, data structures, and data visualization.
- Data analysis, data visualization, Artificial Intelligence (AI), and Machine Learning (ML) are some of the popular uses of Python in Data Science.
- Python offers a plethora of libraries for data analysis including NumPy, Pandas, and SciPy, and for data visualization such as Matplotlib, Plotly, and Seaborn.
- Python is an open-source language, its frameworks and libraries are free to download, and additional resources for Python users include Jupyter Notebook, Anaconda, and Google Colab.
- Python is essential for a variety of roles including Software Engineer, Data Scientist, Coding Engineer, Data Analyst, and Engineering Manager.
- Noble Desktop offers comprehensive programs to learn Python including Data Science Certificate, Software Engineering Certificate, Data Analytics Certificate, Python for Data Science Bootcamp, and more.
- The best ways to learn Python for Data Science include attending live in-person or virtual bootcamps or certificate programs, on-demand or self-paced classes, video seminars or tutorials, and blog posts or articles.
- An in-person or live online course from Noble Desktop can provide comprehensive Python for Data Science training.
Python is one of the most popular programming languages worldwide, especially for Data Science. Web Developers and Software Engineers use Python, but so do Data Scientists, Business Analysts, and Cybersecurity Analysts.
In this overview, you’ll learn more about what Python for Data Science is, what it can do, who uses it, and how to learn it so you can determine how to add this skill to your professional toolbox.
A Brief History of Python for Data Science
Guido van Rossum developed Python in the late 1980s as an improved version of the ABC programming language. With Aaron Watters and James Ahlstrom, van Rossum co-authored internet Programming with Python. This guide was the only available book on Python for many years.
As Python’s popularity grew, it became the primary language for Data Science, data analysis, and Machine Learning. Its open-source ecosystem also made it an ideal choice for web development, prototyping, and scripting. Top companies known to use Python include:
- Cisco
- Intel
- JP Morgan Chase
- Netflix
With its easy syntax and massive worldwide support community, Python’s popularity continues to grow among Data Science and development professionals. If you want to work in the Data Science field, consider starting with Python.
Comparable Programming Languages
Many Data Scientists, Data Analysts, and Machine Learning Engineers use Python more than other programming languages. While some data professionals also have to learn R, Java, and C/C++, Python typically ranks at the top of the list for most of them.
One popular programming language that offers an interesting contrast with Python is JavaScript. Many tech pros learn both of these languages and may even use them together. Python provides an attractive array of Data Science and Machine Learning visualization tools.
Additionally, many tech pros do not consider JavaScript a primary Data Science language, whereas they do use Python for Data Science. Automation in Data Science, in particular, can be easily accomplished with Python.
Comparing and contrasting these languages may be useful only in learning which ones to use for which tasks. When it comes to Data Science, you’ll most likely need to learn at least one or two other languages. Consider starting with Python before moving on to other languages like:
- JavaScript
- SQL
- R
- C/C++
- Java
Learn Python for Data Science with Hands-on Training at Noble Desktop
Because Python for Data Science involves two potentially different disciplines—Python programming and the broader Data Science field—not every student approaches it the same way. How and where you plan to use the knowledge you gain from Python for Data Science training may dictate your approach.
Noble Desktop offers multiple avenues to learn Data Science. Their Data Science Certificate includes Python programming fundamentals, Machine Learning, SQL to query databases, and plotting and dashboard libraries. This program prepares attendees for entry-level positions in Data Science and Python Engineering.
Another option is Noble’s Python for Data Science Bootcamp. A hands-on 30-hour course, the bootcamp includes training in NumPy, Pandas, Matplotlib, and linear regression. Students can save by taking the Python for Data Science Bootcamp as part of the Data Science Certificate program as well.
If you prefer to peruse all the Python for Data Science training Noble Desktop offers, check out the Python Classes page. Here you’ll find bootcamps and certificate programs as well as shorter courses. Top certificate programs include:
- Data Science Certificate
- Software Engineering Certificate
- Data Analytics Certificate
Popular bootcamp options include:
- Python for Data Science Bootcamp
- Python Programming Bootcamp
- FinTech Bootcamp
- Cybersecurity Bootcamp
Other training options include:
- Python for Automation
- Cybersecurity with Python
- Python for Network Security
Noble Desktop’s bootcamps and certificate programs earn high marks from graduates. They are available live online or in-person in New York City. Additional perks include a verified Certificate of Completion and free retakes within a year after graduation. Many certificates and bootcamps also include 1-on-1 mentoring: check course descriptions for more information, including any prerequisites.