This Data Science with Python course will establish your mastery of data science and analytics techniques using Python. With this Python for Data Science Course, you’ll learn the essential concepts of Python programming and gain deep knowledge in data analytics, machine learning, data visualization, web scraping, and natural language processing. Python is a required skill for many data science positions, so jump-start your career with this interactive, hands-on course.
Why learn Data Science with Python?
Python is a multi-paradigm or versatile programming language that can be considered as a sort of swiss knife for the coding world. This is because it supports structured programming, Object-Oriented Programming, and even functional programming patterns. The versatility of Python undoubtedly makes it the best-suited programming language for the data scientists. Here are some of the other advantages of python for data science, which will help you understand why you should learn data science with Python:
- Python is a powerful open-source programming language, which means that it’s free to use while having all the properties that a programming language should have.
- It is a versatile programming language that supports Object-Oriented Programming, Structured Programming, and functional programming patterns.
- Python has some 72,000 libraries in the Python Package Index that aid in scientific calculations and machine learning applications.
- Python sports an easy to understand and readable syntax that ensures that the development time is cut into half when compared with other programming languages.
- Python enables you to perform data analysis, data manipulation, and data visualization, which are very important in data science.
All the above-mentioned advantages of Python programming language make it ideal to be used for data science by the data scientists. Owing to the extensibility and general-purpose nature, it is recommended that you learn data science with Python.
What are the course objectives?
What skills will you learn?
- Gain an in-depth understanding of data science processes, data wrangling, data exploration, data visualization, hypothesis building, and testing. You will also learn the basics of statistics
- Install the required Python environment and other auxiliary tools and libraries
- Understand the essential concepts of Python programming such as data types, tuples, lists, dicts, basic operators and functions
- Perform high-level mathematical computing using the NumPy package and its large library of mathematical functions
- Perform scientific and technical computing using the SciPy package and its sub-packages such as Integrate, Optimize, Statistics, IO, and Weave
- Perform data analysis and manipulation using data structures and tools provided in the Pandas package
- Gain expertise in machine learning using the Scikit-Learn package
- Gain an in-depth understanding of supervised learning and unsupervised learning models such as linear regression, logistic regression, clustering, dimensionality reduction, K-NN and pipeline
- Use the Scikit-Learn package for natural language processing
- Use the matplotlib library of Python for data visualization
- Extract useful data from websites by performing web scrapping using Python
- Integrate Python with Hadoop, Spark, and MapReduce
Who should take this Python for Data Science course?
- Analytics professionals who want to work with Python
- Software professionals looking to get into the field of analytics
- IT professionals interested in pursuing a career in analytics
- Graduates looking to build a career in analytics and data science
- Experienced professionals who would like to harness data science in their fields
- Anyone with a genuine interest in the field of data science
This self-paced course provides 180 days of access to high-quality, self-paced learning content designed by industry experts.
You will receive a course registration confirmation via email shortly after enrollment. If you have questions, please contact us at firstname.lastname@example.org.