Microsoft Data Analysis with Python & R

Overview

AI, Data Science & Cloud Certificates from Google, IBM & Meta — 50% Off

One plan covers every Professional Certificate on Coursera. 50% off Coursera Plus Annual for 10 days only — price increases June 17.

Unlock All Certificates

Build job-relevant data analysis skills using Python, R, and Microsoft tools in this beginner-friendly specialization. You'll learn how to collect, clean, analyze, visualize, and communicate data insights using two of the most popular programming languages in analytics. The program starts with Python programming fundamentals, then moves into data analysis, visualization, generative AI, and machine learning basics. You’ll also learn R programming, tidyverse workflows, data cleaning, and exploratory data analysis using real-world datasets. Through guided labs and practical projects, you’ll use tools such as Jupyter Notebook, Visual Studio Code, GitHub Copilot, pandas, Matplotlib, ggplot2, Scikit-learn, and GitHub. By the end of the specialization, you’ll be able to clean messy datasets, create dashboards and charts, automate analysis workflows, apply beginner machine learning models, and communicate findings clearly. This specialization is ideal for aspiring data analysts, business professionals, career changers, and learners who want practical analytics skills without prior coding experience.

Syllabus

Course 1: Python Programming Fundamentals
Course 2: Data Analysis and Visualization with Python
Course 3: R Programming Essentials with Microsoft Tools
Course 4: Data Manipulation and Cleaning in R
Course 5: Exploratory Data Analysis and Visualization

Courses

0 reviews

View details

Description: This course delves into the world of data analysis with Python. You'll learn how to use libraries like pandas and Matplotlib to manipulate, analyze, and visualize data, extracting valuable insights and communicating findings effectively. Benefits: Become proficient in data analysis techniques, enabling you to extract meaningful insights from data and present them in compelling visualizations. By the end of this course, you'll be able to: • Perform data cleaning, transformation, and manipulation using pandas. • Create various types of visualizations using Matplotlib. • Understand the fundamentals of generative AI and its applications in data analysis. • Implement basic machine learning models for data analysis. Tools/Software: Python, Jupyter Notebook, pandas, Matplotlib, Scikit-learn This course is for entry-Level professionals looking to build a foundational understanding and experience with Python, while seeking employment as a Python developer. No prior work experience or degree is required.
0 reviews

View details

Description: This course lays the groundwork for your Python programming journey. You'll learn essential Python syntax, data structures, and control flow, while practicing debugging and basic code optimization techniques. Benefits: Gain a solid foundation in Python programming, enabling you to write clean, functional scripts and tackle common programming challenges. By the end of this course, you'll be able to: • Write basic Python programs using variables, data types, and operators. • Implement conditional statements and loops to control program flow. • Utilize functions and modules to write reusable and organized code. • Manipulate data using lists, dictionaries, and other data structures. • Debug code and handle errors effectively. • Employ Git for version control and create a professional GitHub portfolio. Tools/Software: Python, Jupyter Notebook, Git, GitHub This course is for entry-Level professionals looking to build a foundational understanding and experience with Python, while seeking employment as a Python developer. No prior work experience or degree is required.
0 reviews

View details

Transform raw data into valuable insights using R's powerful tidyverse tools. This beginner-friendly course introduces you to essential data cleaning and manipulation techniques, making complex data tasks approachable and practical. Learn how to clean messy data, handle missing values, and prepare datasets for analysis using Microsoft's development environment and AI assistance. Through hands-on practice, you'll master fundamental data cleaning skills while building confidence in: - Organizing and structuring data effectively - Handling common data issues - Working with different data formats - Using AI tools to enhance your workflow - Creating reproducible data cleaning processes Each concept is taught step-by-step with extensive examples and guided practice, ensuring you build a strong foundation in data manipulation skills.
0 reviews

View details

Discover the power of data visualization and analysis in this beginner-friendly course. Learn how to turn raw data into meaningful insights using R's visualization tools and Microsoft's development environment. Through hands-on practice, you'll learn to create engaging visualizations and understand basic statistical patterns, all while using AI assistance to enhance your learning. Learn to explore datasets, identify patterns, and communicate insights using ggplot2, Plotly, and R Markdown. Practice univariate, bivariate, and multivariate analysis. Discover the power of data visualization and analysis in this beginner-friendly course. Learn how to turn raw data into meaningful insights using R's visualization tools and Microsoft's development environment. Through hands-on practice, you'll learn to create engaging visualizations and understand basic statistical patterns, all while using AI assistance to enhance your learning.
0 reviews

View details

Begin your R programming journey with this foundational course that combines essential programming concepts with Microsoft's professional development environment. Through five comprehensive modules, you'll master R basics while working with Visual Studio Code and GitHub Copilot. Starting with fundamental concepts like variables and data structures, you'll progress to working with real data and implementing version control. The course features hands-on projects, AI-assisted coding practice, and culminates in creating your first complete R programming project.