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Coursera – How to Use Data Specialization By Brandon Krakowsky

Coursera – How to Use Data Specialization By Brandon Krakowsky

Free Download Coursera – How to Use Data Specialization By Brandon Krakowsky


Released 2/2025
By Brandon Krakowsky
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + subtitle | Duration: 130 Lessons ( 6h 5m ) | Size: 2.6 GB


Analyze Data, Build Models, and Present Insights. Transform data into actionable insights through data analysis, predictive modeling, data visualization, and communication of results.

What you'll learn


Master the process of data wrangling, including data storage, access, and manipulation using SQL.
Perform exploratory data analysis (EDA) using Python, focusing on data inspection, cleaning, visualization, and summarization.
Apply predictive analytics techniques to make data-driven predictions using Python.
Create compelling data visualizations with Tableau for decision-making and storytelling.
Skills you'll gain
Predictive Analytics
Data Analytics
Data Visualization
Python (Programming Language)
Data Science
Tableau (Business Intelligence Software)
Data Storytelling
SQL
Exploratory Data Analysis
Data Analysis
Database Query Tools
Machine Learning
Data Presentation
Data Classification
Logistic Regression
Decision Tree Learning
Random Forest Algorithm
Matplotlib
Seaborn
Pandas (Python Package)
Specialization - 3 course series
"How to Use Data" is designed to equip learners with the essential skills needed for a career in data analytics. This specialization emphasizes the ability to scope and answer critical business questions using data while providing a comprehensive foundation in key data analytics processes. In the first course, you'll explore the fundamentals of data analysis, data science, and data analytics, learning about essential tools and programming languages through real-world case studies. You will master techniques like data wrangling with SQL, gaining hands-on experience with data storage, access, and manipulation using relational databases. Moving into exploratory data analysis (EDA) with Python, you'll develop skills in data inspection, querying, summarization, and visualization. Additionally, you'll learn how to apply predictive analytics techniques—such as regression, decision trees, random forests, and clustering—to solve complex business challenges and make data-driven predictions. Finally, you'll gain expertise in creating impactful visualizations with Tableau and presenting data insights effectively to stakeholders, enabling you to drive informed decision-making in real-world scenarios.
Applied Learning Project
This specialization presents a variety of graded and practice assignments, both in the form of learning checks with multiple attempts, and in the form of programming assignments via Codio platform. Practice assignments in this course don't count towards the Final Grade. All of the other assignmetns are automatically graded, and provide instant feedback to the Learners. Please feel free to post in Discussion Forums located in every Module if you have any questions about the assignments or the instructions. Google Chrome is the recommended browser for completing coding assignments.
Homepage:
https://www.coursera.org/specializations/how-to-use-data













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