Learning Path

Python Programming for Data Science Track

66% of data scientists reported using Python daily, making it the most used tool among analytics professionals. Join them and learn Python basics for Data Science, become versatile with Pandas, and challenge R Programmers in Statistic tasks.

3 Courses
29 Hours in Total
10 Case Studies
Lifetime access to course Content

Market Opportunity

Data science experts expect that Python will be their language of choice, taking into account that it dominates in Deep Learning and Artificial Intelligence applications. And while your journey to learn Python programming may be just beginning, it’s nice to know that employment opportunities are abundant (and growing) as well.

Career Opportunity

Average Data Scientists with Python skills salary annual salary is $91,838 in the United States (source: PayScale)

Highly Demanded

What You Will Learn

  • Learn to program in Python at a good level
  • Learn how to code in Jupyter Notebooks
  • Gain deeper insights into data
  • Use Python to solve common and complex statistical and Machine Learning-related projects
  • How to interpret and visualize outcomes, integrating visual output and graphical exploration
  • Learn hypothesis testing and how to efficiently implement tests in Python
  • Visualise data using methods from histograms to dimensionality reduction.
  • Create, save and serialise data frames in and out of multiple formats.
  • Intersplice, summarise and investigate time series data.
  • Merge data sources into a beautiful whole.
Python A-Z™: Python For Data Science With Real Exercises!
11 hours
Data Manipulation in Python: A Pandas Crash Course
9 hours
Python for Statistical Analysis
9 hours

Other Learning Path

The new powerful tool that will guide you on your educational journey and empower your career with Data Science.

Become a Data Scientist

A true data scientist is someone who can define a problem statement that can be solved using data and then successfully solve it using the knowledge and expert skills in data mining, cleaning, analyzing, and interpreting.

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Machine Learning Track

A machine learning (ML) engineer is an expert on using data to training models. The models are then used to automate processes like image classification, speech recognition, and market forecasting.

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