Python is one of the most popular programming languages for data science, thanks to its flexibility, ease of use, and string support for data manipulation, analysis, and visualization libraries.
python
IS a high level, general-purpose programming language that is widely used for various applications such as web development, scientific computing, data analysis, artificial intelligence, and many more. It was created in the late 1980s by Guido van Rossum and was first released in 1991.
Python has a simple and easy-to-learn syntax, which makes it a popular language for beginners. It emphasizes readability and clean code, which makes it easier to maintain and collaborate with other programs. Python is an interpreted language, which means that the code is executed line by line without the need for compilation, making it easy to test and debug.
One of the most significant strengths of python is its vast and active community, which has created numerous libraries and modules for various purposes. These include Numpy and pandas for scientific computing and data analysis, Matplotib and seaborn for data visulaization, scikit-learn and tensor flow for machine learning and artificial intelligence, and Django and flask for web development.
Python Course Details:
Certificate course in Python is a short term course, which is generally of 5-6 months Duration. There is no specified eligibility criterion to admission for python course, if students are still expected to have a basic knowledge of computer programming course. This course’s motive is to provide basic knowledge and skills of python language for students.
Python Course Details:
Course | Python |
Eligibility | NO |
duration | 3-6 months |
Python Course Fee | INR 20,000 TO INR 45,000 for the course |
Course type | Certification |
Starting salary expected | INR 30,000 TO INR 70,000 |
Employment opportunities | Software developer, web application developer, software programmer, and etc |
Skills of Python
Python is a versatile programming language that can be used for a variety of applications, including web development, scientific computing, data analysis, artificial intelligence, machine learning, and more. Here are some essential skills for using python effectively:
● Understanding basic syntax: This includes knowledge of variables, data types, operators, control flow statements, functions. And input/output.
● Familiarity with Python libraries: Python has many powerful libraries and frameworks for various applications. Understanding and being able to use these libraries effectively can greatly enhance your python skills.
● Object-oriented programming: Python is an object-oriented programming language, which means that understanding object-oriented principles such as classes, inheritance, and polymorphism is essential for writing robust and scalable code.
● Data structures and algorithms: Understanding data structures such as lists, dictionaries, and sets, as well as algorithms such as sorting and searching, is important for solving complex programming problems.
● Collaboration and version control: Python is often used in collaborative projects, and being able to work with others effectively and use version control tools such as Git can greatly enhance your productivity and code quality.
● Problem-solving and critical thinking: Like any programming language, Python requires problem-solving and critical thinking skills to write effective and efficient code.
Python for Data Science
Python is a popular programming language used for data science because of its simplicity, versatility, and powerful libraries. Here are some key libraries and tools in Python used for data science:
1. NumPy: NumPy is a library for working with numerical data in Python. It provides functions for performing mathematical operations on arrays and matrices, which are commonly used in data analysis and machine learning.
2.Pandas: Pandas is a library for data manipulation and analysis. It provides data structures for handling structured data, such as data frames, and includes functions for filtering, grouping, and aggregating data.
3.Matplotlib: Matplotlib is a library for creating visualizations in Python. It provides functions for creating a wide range of graphs and plots, including line graphs, scatter plots, and histograms.
4.Seaborn: Seaborn is a library built on top of Matplotlib that provides more advanced visualizations for statistical data analysis.
5. Scikit-learn: Scikit-learn is a library for machine learning in Python. It provides functions for common machine learning tasks, such as classification, regression, and clustering.
6.TensorFlow and PyTorch: TensorFlow and PyTorch are two popular libraries for deep learning in Python. They provide tools for building and training neural networks for tasks such as image recognition and natural language processing.
Top 10 Best Python Courses
Course Name | Provider | Course Fees |
Learn Intermediate Python | Udacity | Subscription-Based |
Certified Python Master Developer Course | Henry Harvin | – |
Python for Everybody | Coursera | INR 3,878 (1 Month) INR 7,757 (3 Months) INR 11,636 (6 Months) |
Google IT Automation with Python | Google via Coursera | INR 1,108 (1 Month) INR 2,216 (3 Months) INR 3,324 (6 Months) |
Python 3 Programming Specialisation | Coursera | INR 3,878 (1 Month) INR 7,757 (3 Months) INR 11,636 (6 Months) |
2023 Complete Python Bootcamp From Zero to Hero in Python | Udemy | INR 455 ( |
Machine Learning A-Z: Hands-on Python and R in Data Science | Udemy | INR 649 ( |
Introduction to Python Programming | edX | INR 42,584 |
Python Certification Course | Simplilearn | Subscription-Based |
Python Certification Course | Intellipaat | INR 12,996 (Self-Paced Training) INR 20,007 (Online Classroom) |
Python Tutorials for Beginners
Course name | Provider | Python course fees |
Complete Python Tutorial for Beginner | Udemy | INR 455 ( |
Python Tutorial | Tutorials Point | – |
Python Tutorial | W3School | – |
Learn Python Tutorial | Java Point | – |
Python Tutorial | LearnPython.org | – |
Conclusion
Python is an excellent language for data science due to its simplicity, versatility, and the large number of libraries available for data manipulation, analysis, visualization, and machine learning. With the use of popular libraries such as NumPy, Pandas, Matplotlib, Seaborn, Scikit-learn, Tensor Flow, and PyTorch, Python has become a go-to language for data scientists and analysts in various fields. Whether you are working with large datasets, building machine learning models, or visualizing data, Python has the tools to make your work easier and more efficient.