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5 Python Courses for Your Data Science Career

Data science is a popular choice for those looking for an exciting career that offers excellent growth prospects, tremendous learning and great pay packages. Huge amounts of data flow daily to organizations of all sizes and in all industries, and insights from this data help to measure progress, make informed decisions and plan for the future. A data scientist is someone equipped to process and organize the data with algorithms, scientific methods and other techniques.

In the course of a data science career, it is beneficial to have a strong base in programming. Knowing more than one programming language is advisable, but aspiring data science professionals must be skilled in at least one. And, given that Python is one of the most widely used, it makes sense to learn how to work with Python.

Here are five Python courses available:

Applied Data Science with Python (Coursera)

A five-month, seven-hours-a-week course offered by the University of Michigan, this program comprises five lessons introducing the learner to the Python programming language. It includes the following sub-topics within Python:

  • Programming basics
  • Data science
  • Charting and data representation
  • Applied machine learning

This specialization is targeted at intermediate learners who want to apply statistics, machine learning, text analysis and social network analysis techniques by using the popular Python toolkits in their data science careers.

The key advantages of this course are as follows:

  • Mastery of Python programming skills
  • Learning how to conduct an inferential statistical analysis and analyze social network connectivity
  • Application of data science methods and techniques
  • Usage of applied machine learning concepts to enhance data analysis skills
  • Hands-on projects to enhance skills
  • Completion certificate

Introduction to Python for Data Science (Datacamp)

This four-hour Datacamp course is excellent to gain a strong command on the basics of data analysis in Python and learn scientific computing with NumPy, a library for the Python language. Designed in particular to teach aspiring data science professionals the usage and implementation of Python for data science, it covers:

  • Data storage and manipulation techniques
  • Data science tools to begin own analyses
  • And various concepts like Python Basics, Python Lists, Functions and Packages, and NumPy

The key advantages of this course are as follows:

  • Interactive nature lets students learn how to use Python both interactively and through a script to create their first variables
  • It covers storage, access and manipulation of data in lists, facilitating work with huge amounts of data
  • Students can learn about the NumPy Python package and how to work with the NumPy array
  • 57 exercises and 11 videos
  • Completion certificate

Python A-Zā„¢: Python for Data Science (Udemy)

Among the best online courses for a data science career, this is an 11-12 hour course requiring two to three hours a week. It teaches the student how to begin programming in Python, core programming principles and other topics. The course offers not just detailed knowledge of Python for data science but also the ability to implement real-life scenarios.

The key advantages of this course are as follows:

  • Step-by-step training of every tutorial
  • Learning about core programming principles and coding in Jupyter Notebooks
  • Knowledge of integer, float, logical, string, and other types in Python
  • Knowledge of for() and while() loops
  • A new variable concept after every video
  • Real-life analytical challenges
  • Certificate of completion

Python Data Science Certification Program (edX)

This two to four month course is a great way to become a data science professional. It includes five courses covering Python basics along with data analysis and data visualization. Also including hands-on exercises, it is a good choice even for those new to the field.

The key advantages of this course are as follows:

  • Knowledge of Python basics and its application to data science
  • Data visualizations with Matplotib, Folium and Seaborn
  • Data analysis using Python Pandas and NumPy libraries
  • Iterative data science using Jupyter Notebooks on IBM Cloud
  • Self-paced program
  • Completion certificate

Python for Data Science (Emeritus)

This two-month course requires two to four hours a week and is great for those without any prior Python programming experience. Covering the usage of Python for data analysis and insight generation, it includes:

  • Over 124 recorded video lectures
  • Eight live online teaching sessions
  • Two career guidance sessions from instructors

The key advantages of this course are as follows:

  • Knowledge of Python basics, including variables and types, subsetting lists, manipulating lists, functions, methods and NumPy
  • Basic plots with Matplotlib, Histograms, Dictionaries, Boolean Operators, While Loop and Four Loop, and Distribution
  • Data manipulation with Pandas using indexing, slicing, filtering and pivoting data frames
  • Data visualization using multiple graphs, customizing axes, 2D arrays and visual regression
  • Useful projects and assignments

Apart from taking a course in Python, aspiring data science professionals can also opt to receive some of the best data science certifications offered by the Data Science Council of America (DASCA). DASCA researches, designs and builds platform-independent data science knowledge frameworks, standards and credentials. They reflect industry-leading initiatives to elevate the quality of data science professionals for the organizations of the world. DASCA certifies individuals entering or working across the spectrum of emerging data science professions.

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