The Ultimate Data Science (Python & R) Course: All In One
The Ultimate Data Science (Python & R) Course: All In One, available at $59.99, has an average rating of 4.35, with 73 lectures, based on 18 reviews, and has 150 subscribers.
You will learn about Gain a comprehensive understanding of data science principles and methodologies. Master key data science concepts essential for analysis and problem-solving. Achieve proficiency in data manipulation and analysis using Python Pandas. Develop the ability to create interactive visualizations with Bokeh. Learn efficient package management techniques for streamlined workflows. Understand and implement machine learning algorithms using Scikit-Learn. Analyze data effectively using the most powerful data science stack available. Perform data cleaning, sorting, classification, clustering, and regression tasks. Conduct dataset modeling and prediction with confidence using Anaconda. Enhance problem-solving skills for business applications through data science. This course is ideal for individuals who are Web Developers or Software Developers or Programmers or Anyone interested in Data Science It is particularly useful for Web Developers or Software Developers or Programmers or Anyone interested in Data Science.
Enroll now: The Ultimate Data Science (Python & R) Course: All In One
Summary
Title: The Ultimate Data Science (Python & R) Course: All In One
Price: $59.99
Average Rating: 4.35
Number of Lectures: 73
Number of Published Lectures: 73
Number of Curriculum Items: 73
Number of Published Curriculum Objects: 73
Original Price: $199.99
Quality Status: approved
Status: Live
What You Will Learn
- Gain a comprehensive understanding of data science principles and methodologies.
- Master key data science concepts essential for analysis and problem-solving.
- Achieve proficiency in data manipulation and analysis using Python Pandas.
- Develop the ability to create interactive visualizations with Bokeh.
- Learn efficient package management techniques for streamlined workflows.
- Understand and implement machine learning algorithms using Scikit-Learn.
- Analyze data effectively using the most powerful data science stack available.
- Perform data cleaning, sorting, classification, clustering, and regression tasks.
- Conduct dataset modeling and prediction with confidence using Anaconda.
- Enhance problem-solving skills for business applications through data science.
Who Should Attend
- Web Developers
- Software Developers
- Programmers
- Anyone interested in Data Science
Target Audiences
- Web Developers
- Software Developers
- Programmers
- Anyone interested in Data Science
Embark on an Unforgettable Journey into the World of Data Science and Machine Learning
Unlock the transformative power of data science and machine learning with our comprehensive course, designed to elevate your expertise and set you apart in the competitive landscape. Delve deep into the essential aspects of bias avoidance, model interpretability, and more, gaining in-demand skills that are crucial in today’s data-driven world.
Experience the Power of Anaconda: Your Ultimate Data Science Companion
This course invites you to explore Anaconda, the premier open-source platform that integrates the best tools for data science professionals. Anaconda supports over 100 popular packages and languages, including Python, Scala, and R, streamlining your data science operations for real-world applications. Ideal for data analysts and professionals, this course requires a foundational knowledge of Python and basic data science principles.
Master the Art of Solving Business Problems with Data Science
Our meticulously crafted syllabus covers the full spectrum of data science, ensuring you gain comprehensive knowledge and practical skills. From Python, Pandas, and Scikit-learn to Keras, Prophet, statsmod, and SciPy, you’ll become proficient in the tools and techniques that drive the field. Additionally, you’ll master statistics and probability, fundamental to data science, and unlock the power of data visualization with Seaborn, Matplotlib, and Plotly.
Course Highlights:
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A Comprehensive Introduction to Data Science: Lay a solid foundation with an in-depth introduction to the world of data science.
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Master Key Data Science Concepts: Grasp the essential concepts that form the backbone of data science.
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Unlock the Secrets of Python Pandas: Become adept at data manipulation and analysis with Python Pandas.
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Explore the World of Bokeh: Learn how to create interactive and visually appealing plots using Bokeh.
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Effortless Package Management: Simplify your workflow with efficient package management techniques.
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Demystify Machine Learning with Scikit-Learn: Gain proficiency in machine learning algorithms and applications using Scikit-Learn.
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Master Data Analysis with the Most Powerful Data Science Stack: Leverage the full power of Anaconda’s data science stack for effective data analysis.
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Perform Data Cleaning, Sorting, Classification, Clustering, Regression, and Dataset Modeling: Acquire hands-on experience in essential data science tasks using Anaconda.
By the end of this course, you will possess unparalleled expertise in data science, empowering you to excel in data-driven decision-making. Join us on this exhilarating journey and transform your career today!
What You’ll Learn:
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Introduction to Data Science: Gain a broad understanding of the data science landscape.
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Key Data Science Concepts: Learn and understand the critical concepts that underpin data science.
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Python Pandas: Unlock the capabilities of Python Pandas for data manipulation and analysis.
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Bokeh: Master the use of Bokeh for creating stunning visualizations.
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Package Management: Efficiently manage data science packages.
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Machine Learning with Scikit-Learn: Understand and apply machine learning techniques using Scikit-Learn.
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Powerful Data Science Stack: Analyze data efficiently using the most robust data science tools available.
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Data Cleaning and Modeling: Perform essential tasks such as cleaning, sorting, classification, clustering, regression, and dataset modeling using Anaconda.
Enroll now to embark on a journey that will not only enhance your data science skills but also transform your professional trajectory.
Course Curriculum
Chapter 1: Welcome
Lecture 1: Introduction
Lecture 2: Welcome Message
Chapter 2: Getting Started
Lecture 1: Learn About Anaconda Installation
Lecture 2: Using Python via Jupyter
Lecture 3: Learning Jupyter Basics
Lecture 4: Learning Python Pandas – Learn How to Analyze Data
Lecture 5: Learning Bokeh Basics – Learn How to Visualize Data
Lecture 6: Machine Learning with Scikit-Learn
Chapter 3: Data Science – Understanding the Key Concepts
Lecture 1: Introduction
Lecture 2: Empowering the Data Science team
Lecture 3: Understanding Data Science Development Workflow
Chapter 4: Data Science – Learning Python Pandas
Lecture 1: Learn About Pandas DataFrames
Lecture 2: Python Pandas – Creating Columns & Modifying Data
Lecture 3: Understanding Data Selection – Boolean Masks
Lecture 4: Learn How to Read Data – Part 1
Lecture 5: Learn How to Read Data – Part 2
Lecture 6: Learn How to Group Data Together
Lecture 7: Learn How to Connect to a Database – Part 1
Lecture 8: Learn How to Connect to a Database – Part 2
Lecture 9: Learn About Time Series Data
Lecture 10: Using Pandas to Read and Write Files
Lecture 11: Section Summary
Chapter 5: Data Science – Introduction to Anaconda Platform
Lecture 1: Python & R Open Source Analytics
Lecture 2: Learn and Understand Conda
Lecture 3: Learn About Anaconda Components
Lecture 4: Parallel Data Processing
Lecture 5: Learning Data Science Workflows
Lecture 6: Creating a New Project
Chapter 6: Data Science – Learn and Understand Bokeh
Lecture 1: Introduction
Lecture 2: Bokeh – Learn How to Plot Pandas DataFrames
Lecture 3: Bokeh – Learn How to Manage Plot Construction – 1
Lecture 4: Bokeh – Learn How to Manage Plot Construction – 2
Lecture 5: Learn How to Add Additional Widgets – 1
Lecture 6: Learn How to Add Additional Widgets – 2
Lecture 7: Learn How to Create Web Plots
Lecture 8: Section Summary
Chapter 7: Data Science – Learn How to Manage Packages
Lecture 1: Introduction
Lecture 2: Learn How to Add Channels
Lecture 3: Learn More About Packages
Lecture 4: Learn How to Create a New Environment
Lecture 5: Learning Conda environments in Jupyter kernels
Lecture 6: Learning the Command Line – Part 1
Lecture 7: Learning the Command Line – Part 2
Lecture 8: Learn and Understand pip & conda – Part 1
Lecture 9: Learn and Understand pip & conda – Part 2
Lecture 10: Learn About Conda update
Lecture 11: Learn More About Conda Environments
Lecture 12: Section Summary
Chapter 8: Data Science – Data Visualization and Data Processing
Lecture 1: Introduction
Lecture 2: Accessing and Processing Data – Part 1
Lecture 3: Accessing and Processing Data – Part 2
Lecture 4: ggplot – Learn How to Create Visualizations – Part 1
Lecture 5: ggplot – Learn How to Create Visualizations – Part 2
Lecture 6: Predictive Models – Learn How to Build Linear Models – Part 1
Lecture 7: Predictive Models – Learn How to Build Linear Models – Part 2
Lecture 8: Learn How to Create Interactive Visualizations
Lecture 9: Section Summary
Chapter 9: Data Science – Exploring Scikit-Learn
Lecture 1: Introduction
Lecture 2: Predictive Models – Learn How to Generate Predictions
Lecture 3: Predictive Models – Let's Score the Models
Lecture 4: Section Summary
Chapter 10: Data Science – Using Fusion and Mosaic to Solve Problems
Lecture 1: Introduction
Lecture 2: Learn About Fusion Installation
Lecture 3: Learn to Use Fusion Server
Lecture 4: Learn About Data Integration
Lecture 5: Learn About Mosaic Installation
Lecture 6: The Demo
Chapter 11: Dask – Scalable Analytics in Python
Lecture 1: Introduction to Dask
Lecture 2: Dask – Learn About Dask Dataframes – Part 1
Lecture 3: Dask – Learn About Dask Dataframes – Part 2
Lecture 4: Section Summary
Chapter 12: Course Summary
Lecture 1: Summary
Chapter 13: Course Material & Source Code
Lecture 1: Course Material & Source Code
Instructors
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Justin Lambert
Data Scientist & Computer Vision Engineer
Rating Distribution
- 1 stars: 1 votes
- 2 stars: 0 votes
- 3 stars: 0 votes
- 4 stars: 3 votes
- 5 stars: 14 votes
Frequently Asked Questions
How long do I have access to the course materials?
You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!
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