Python is a very powerful programming language used for data science and many other applications. Python is often the choice for developers who need to apply statistical techniques or data analysis in their work, or for data scientists whose tasks need to be integrated with web apps or production environments. Its combination of machine learning libraries and flexibility makes Python uniquely well-suited to developing sophisticated models and prediction engines that plug directly into production systems. Data Scientist has been ranked the number one job on Glassdoor and the average salary of a data scientist is over $120,000 in the United States according to Indeed! Data Science is a rewarding career that allows you to solve some of the world’s most interesting problems. Today our team experts have researched the best Python courses for data science into the following list:
Python Course For Data Science [Best Value]
Programming for Data Science with Python [Udacity]
Rating: 4.7 / 5
Duration: 3 Months
Learn the programming fundamentals required for a career in data science. By the end of the program, you will be able to use Python, SQL, Command-Line, and Git. There are no prerequisites for this program, aside from basic computer skills. You should feel comfortable performing basic operations on your computer (e.g., opening files, folders, and applications, copying and pasting).
- Learn SQL fundamentals such as JOINs, Aggregations, and Subqueries. Learn how to use SQL to answer complex business problems.
- Learn Python programming fundamentals such as data structures, variables, loops, and functions. Learn to work with data using libraries like NumPy and Pandas.
- Learn how to use version control and share your work with other people in the data science industry.
Introduction to Python [DataCamp]
This course focuses on Python specifically for data science. In this Python course, you’ll learn about powerful ways to store and manipulate data, and helpful data science tools to begin conducting your own analyses.
- Learn how to use Python interactively and by using a script. Create your first variables and acquaint yourself with Python’s basic data types.
- Learn how to store, access, and manipulate data in lists: the first step toward efficiently working with huge amounts of data.
- Learn how to use functions, methods, and packages to efficiently leverage the code that brilliant Python developers have written.
- learn to work with powerful tools in the NumPy array, and get started with data exploration.
Professional Certificate in Python Data Science [EDX]
This Data Science with Python program is aimed at preparing you for a career in data science and machine learning. This program is taught by experts and focused on hands-on learning and job readiness.
You will start by learning Python. You will then develop skills for data analysis and data visualization and also get a practical introduction to machine learning. Finally, you will apply and demonstrate your knowledge of data science and machine learning with a capstone project involving a real life business problem.
- Understand Python language basics and how they apply to data science.
- Practice iterative data science using Jupyter notebooks on IBM Cloud.
- Analyze data using Python libraries like pandas and numpy.
- Create stunning data visualizations with matplotlib, folium, and seaborn.
- Build machine learning models using scipy and scikitlearn.
- Demonstrate proficiency in solving real life data science problems.
Python for Everybody Specialization [Coursera]
This Specialization builds on the success of the Python for Everybody course and will introduce fundamental programming concepts including data structures, networked application program interfaces, and databases, using the Python programming language. In the Capstone Project, you’ll use the technologies learned throughout the Specialization to design and create your own applications for data retrieval, processing, and visualization.
- Cover the basics of how one constructs a program from a series of simple instructions in Python.
- Introduce the core data structures of the Python programming language.
- Show how one can treat the Internet as a source of data. Scrape, parse, and read web data as well as access data using web APIs.
- Introduce students to the basics of the Structured Query Language (SQL) as well as basic database design for storing data as part of a multi-step data gathering, analysis, and processing effort.
- Students will build a series of applications to retrieve, process and visualize data using Python.
The Data Science Course 2022: Complete Data Science Bootcamp [Udemy]
This course created by 365 Careers is the #1 best-selling provider of business, finance, and data science courses on Udemy. The company’s courses have been taken by more than 1,750,000 students. This course provides the entire toolbox you need to become a data scientist. No prior experience is required. This course will start from the very basics. With this course you will fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow.
- Understand the mathematics behind Machine Learning.
- Perform linear and logistic regressions in Python
- Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
- Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
- Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
- Start coding in Python and learn how to use it for statistical analysis
Python for Data Science and Machine Learning Bootcamp [Udemy]
This comprehensive course will be your guide to learning how to use the power of Python to analyze data, create beautiful visualizations, and use powerful machine learning algorithms.
This course is designed for both beginners with some programming experience or experienced developers looking to make the jump to Data Science.
- Use Python for Data Science and Machine Learning
- Use Spark for Big Data Analysis
- Implement Machine Learning Algorithms
- Learn to use NumPy, Matplotlib, and Seaborn
- Use Plotly for interactive dynamic visualizations
- Use SciKit-Learn for Machine Learning Tasks
Predictive Data Analysis with Python [Educative]
In this course, you will learn how to perform predictive data analysis using Python. The ideal audience is those who want to start their careers as data analysts. The main goal of this course is to show you how to use statistics to draw useful insights from data which can help in prediredicting future behavior or patterns.
- Start learning immediately instead of fiddling with SDKs and IDEs. It‘s all on the cloud.
- Learn how to create stunning visualizations that you can use for reports.
- You’ll learn all the tools of the trade that data scientists use everyday including: NumPy, Pandas, Matplotlib, and Seaborn.
Python Data Analysis [Linkedin]
In this course, instructor Michele Vallisneri shows you how, explaining what it takes to get started with data science using Python. Michele demonstrates how to set up your analysis environment and provides a refresher on the basics of working with data structures in Python. Then, he jumps into the big stuff: the power of arrays, indexing, and tables in NumPy and pandas. He also walks through two sample big-data projects: using NumPy to identify and visualize weather patterns and using pandas to analyze the popularity of baby names over the last century.
- Installation and Setup
- Data Structures in Pure Python
- Wordplay: Anagrams and Palindromes
- Arrays with NumPy
- Use Case: Weather Data
- Use Case: Baby Names
Applied Data Science with Python Specialization [Coursera]
The 5 courses in this University of Michigan specialization introduce learners to data science through the python programming language. This skills-based specialization is intended for learners who have a basic python or programming background, and want to apply statistical, machine learning, information visualization, text analysis, and social network analysis techniques through popular python toolkits such as pandas, matplotlib, scikit-learn, nltk, and networkx to gain insight into their data.
- Conduct an inferential statistical analysis
- Discern whether a data visualization is good or bad
- Enhance a data analysis with applied machine learning
- Analyze the connectivity of a social network
Data Science with Python Certification [Edureka]
This course will enable you master important Python programming concepts such as data operations, file operations, object-oriented programming, and various Python libraries. This course is well suited for professionals and beginners. Make you understand the different types of Machine Learning, Recommendation Systems.
- Get a brief idea of what it is and touch on the basics
- Learn different types of sequence structures, related operations, and their usage. Also learn diverse ways of opening, reading, and writing to files.
- Learn how to create generic scripts, how to address errors/exceptions in code, and finally how to extract/filter content using Regex.
- Get familiar with the basics of statistics, different types of measures and probability distributions, and the supporting libraries that assist in these operations.
- Learn the concept of Machine Learning and its types.
Finally, We hope this list helps you choose the best one for you. Don’t miss to check available discounts for your provider before purchasing the course.