Python is the most popular programming language used for Data Science due to its support for various libraries and popular frameworks. Their syntax and functions are some of the easiest compared to other programming languages.
This course by Udacity offers the best resources to train you in Python for Data Science. Their right learning content, mini-projects, career service, and mentor support make this the best course to learn Python for data science.
Hence to help you understand why this course is best to learn Python for data science, we have made Programming for Data Science with Python Udacity review.
The path to becoming a Data Scientist begins by learning Python. But that alone won’t be sufficient to get started with the Data Science course. One should also know SQL and Git.
Is Python Good for Data Science?
A recent survey conducted across the globe showed that more than 83% out of 24000 data scientists use Python. Any data science enthusiast should pursue learning Python first.
Python is a dynamic and general-purpose language that is very simple to learn and supports various external libraries. Due to its excellent ETL process, it is the most preferred language compared to the R language.
Another reason for choosing to learn Python over R is because when it comes to data manipulation R lags behind.
Are there any prerequisites before taking the course Programming for Data Science with Python? No, anyone from any background can learn the Python programming language.
Udacity Programming for Data Science with Python Review
This Programming for Data Science with Python Nanodegree from Udacity is not only designed to teach you Python but also SQL, Git, and command line. The course curriculum is carefully crated by collaborating with Mode.
The essential tools required for modern data scientists and languages are taught in this Nanodegree program.
The course has 3 parts in its syllabus along with mini projects in each section.
Introduction to SQL
Once you enroll, you’ll begin your online training in SQL. SQL stands for a Structured Query Language, used to manage data in a database. Learning SQL opens up wide career opportunities such as Software Engineer, Data Engineer, Machine Learning, AI, and more.
In this first section of Nanodegree, you are taught the fundamentals of SQL. This training will help you further while programming in Python to manage the data.
The mini-project here involves you working on the relational databases while working with PostgreSQL. We’ve also listed several SQL mini-projects that will help you understand the working of SQL efficiently.
Introduction to Python Programming
Once you are taught the basics of SQL, you’ll next proceed to learn Python programming. The course teaches you from the scratch and from the beginning.
The fundamentals of Python are very important to keep in mind while you learn. As you progress towards learning the syntax of the different functions of Python, the basic fundamentals will come in handy. You’ll be surprised and amazed by Python’s simplicity and its amazing capability to solve a problem.
Along with learning different kinds of loops and functions, you are also trained on using popular Python libraries such as Pandas and NumPy. Both these are essential in Data Science hence make sure you provide extra attention in these sections.
After the second section is complete you’ll then work on the Python project. Here the project involves you writing a script in Python to collect and compute the data.
Introduction to Version Control
The final part of the Programming for Data Science with Python is version control. Version control in coding involves you writing a code with few modifications and saving them differently.
This helps you understand how the different versions of the code provide different outputs. And it is also helpful in sharing your code with other people.
Github is a great skill that every programmer should and will have. The project in this course will teach you the essential tools that every programmer should know.
You will learn to use Git and Github to manage different versions of the code while allowing you to collaborate with other software engineers or data scientists.
Once you finish all three sections along with all the projects, you will get a Certificate from Udacity which is recognized by several top companies.
Pros and Cons of Python for Data Science
- It is one of the easiest programming languages to learn the best choice to learn for beginners.
- Python is a dynamic and general-purpose language.
- It has many inbuilt and third-party libraries to support and solve many problems.
- Python API is provided by many online services.
- Popular Python packages such as pandas, Tensorflow, and scikit-learn are used for advanced machine learning applications.
- R’s excellent statistical and data analysis packages dwarf the Python language.
- Python is a dynamically typed language. Which means you must show due care when typing. You can expect a Type error from time to time.
Features of Udacity Programming for Data Science with Python Nanodegree Review
Every Udacity Nanodegree course comes with all the below features:
- Every student gets technical mentor support who will assist you to stay on track with the course.
- All the projects that you work on are carefully designed and chosen from real-world projects. This helps you develop job-ready skills for Python and Data Science.
- Students signing up on the Udacity platform are entitled to career service, where you get advice when they review your professional profile and your resume.
- Offers a great flexible learning program.
These features make the Programming for Data Science with Python Udacity course to be very engaging.
Summary: Is Programming for Data Science with Python Worth Taking?
We definitely recommend taking the Programming for Data Science with Python Udacity course. Their unique offers and features are what make the Udacity learning platform the best.
Their service to review your resume will help you a lot with their constant feedback and mentor support is an excellent addition.
We hope this Programming for Data Science with Python Udacity review was helpful for you to make your decision. Also, another important reason to take Udacity is their certification is recognized by many organizations, and your chance to get hired increases.
Programming for Data Science with Python
Python is a dynamic and general-purpose language that is very simple to learn and supports various external libraries. Hence course is an excellent choice to learn Python for Data Science.
Course Provider: Organization
Course Provider Name: Udacity
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