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Teachable VS NumPy

Compare Teachable VS NumPy and see what are their differences

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Teachable logo Teachable

Create and sell beautiful online courses with the platform used by the best online entrepreneurs to sell $100m+ to over 4 million students worldwide.

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python
  • Teachable Landing page
    Landing page //
    2023-04-17
  • NumPy Landing page
    Landing page //
    2023-05-13

Teachable features and specs

  • Ease of Use
    Teachable offers a user-friendly interface that allows users to create and manage online courses without needing any technical knowledge.
  • Customization
    Teachable provides a variety of customization options for course creators to tailor the look and feel of their courses and sales pages.
  • Integrated Payment Processing
    Teachable simplifies the process of monetizing courses by offering integrated payment processing with support for multiple currencies.
  • Analytics and Reporting
    Users have access to comprehensive analytics and reporting tools to track student engagement, sales, and overall course performance.
  • Marketing Tools
    Teachable includes built-in marketing tools such as affiliate programs, coupon codes, and email marketing integrations to help creators promote their courses.
  • Security and Hosting
    Teachable handles the hosting and security of online courses, ensuring that content is protected and accessible to students 24/7.
  • Multiple Content Formats
    Users can incorporate various types of content into their courses, including videos, quizzes, assignments, and downloadable resources.

Possible disadvantages of Teachable

  • Pricing
    Teachable's pricing plans can be expensive, especially for smaller course creators or those just starting out.
  • Transaction Fees
    Lower-tier plans come with transaction fees, which can cut into the earnings of course creators.
  • Limited Advanced Customization
    While Teachable offers some customization options, advanced users may find the customization capabilities limited compared to self-hosted platforms.
  • Email Support
    Customer support is primarily provided via email, which can result in slower response times compared to live chat or phone support.
  • Lack of Community Features
    Teachable does not offer robust community features, such as forums or social media-like interaction, which can enhance student engagement.
  • Learning Curve for Advanced Features
    Although the platform is user-friendly, some advanced features may have a steeper learning curve for users who are not tech-savvy.
  • Dependence on Platform
    Course creators are dependent on Teachable for hosting and managing their content, meaning any issues with the platform can affect their courses.

NumPy features and specs

  • Performance
    NumPy operations are executed with highly optimized C and Fortran libraries, making them significantly faster than standard Python arithmetic operations, especially for large datasets.
  • Versatility
    NumPy supports a vast range of mathematical, logical, shape manipulation, sorting, selecting, I/O, and basic linear algebra operations, making it a versatile tool for scientific and numeric computing.
  • Ease of Use
    NumPy provides an intuitive, easy-to-understand syntax that extends Python's ability to handle arrays and matrices, lowering the barrier to performing complex scientific computations.
  • Community Support
    With a large and active community, NumPy offers extensive documentation, tutorials, and support for troubleshooting issues, as well as continuous updates and enhancements.
  • Integrations
    NumPy integrates seamlessly with other libraries in Python's scientific stack like SciPy, Matplotlib, and Pandas, facilitating a streamlined workflow for data science and analysis tasks.

Possible disadvantages of NumPy

  • Memory Consumption
    NumPy arrays can consume large amounts of memory, especially when working with very large datasets, which can become a limitation on systems with limited memory capacity.
  • Learning Curve
    For users new to scientific computing or coming from different programming backgrounds, understanding the intricacies of NumPy's operations and efficient usage can take time and effort.
  • Limited GPU Support
    NumPy primarily runs on the CPU and doesn't natively support GPU acceleration, which can be a disadvantage for extremely compute-intensive tasks that could benefit from parallel processing.
  • Dependency on Python
    Since NumPy is a Python library, it depends on the Python runtime environment. This can be a limitation in environments where Python is not the primary language or isn't supported.
  • Indexing Complexity
    Although NumPy's slicing and indexing capabilities are powerful, they can sometimes be complex or unintuitive, especially for multi-dimensional arrays, leading to potential errors and confusion.

Teachable videos

+ Add

Why I Love Using Teachable 🎓 Best Online Course Platform? (TEACHABLE REVIEW)

More videos:

  • Review - Thinkific vs Teachable: Which is Course Builder is Better?
  • Review - 🦋Teachable Review Online Course Builder Honest Opinion

NumPy videos

+ Add

Learn NUMPY in 5 minutes - BEST Python Library!

More videos:

  • Review - Python for Data Analysis by Wes McKinney: Review | Learn python, numpy, pandas and jupyter notebooks
  • Review - Effective Computation in Physics: Review | Learn python, numpy, regular expressions, install python

Category Popularity

0-100% (relative to Teachable and NumPy)

Teachable

NumPy

Education
100 100%
Education
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
LMS
100 100%
LMS
0% 0
Data Science Tools
0 0%
Data Science Tools
100% 100

User comments

Share your experience with using Teachable and NumPy. For example, how are they different and which one is better?
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Reviews

These are some of the external sources and on-site user reviews we've used to compare Teachable and NumPy

Teachable Reviews

9 Teachable Alternatives in 2024 Ranked
Success in a digital learning space requires the right choice of platforms for creating and managing course content. Choosing a suitable alternative to Teachable will offer a diversified set of features for different needs and budgets. From free plans for beginners to features for expert teachers, we have ranked the best nine Teachable alternatives to help you choose. Read...
Source: teach.io
8 best Teachable alternatives for course creators (Features & pricing)
That said, Teachable is very limited in the product types and customization options it offers creators. Most of the successful course creators on Teachable use third-party tools for email marketing, landing page builders, or building a website.
Source: www.podia.com
The Top Free and Paid Teachable Alternatives For Creators
Tl;DrKnown as Top Features Pricing plansAll-in-one platform for digital products Starts at $36/month (billed annually) Online course marketplaceFree; charges percentage commissions on each saleOnline community platform for creatorsStarts at $89/month (billed annually)Creator monetization platform Free: 5% of Patreon income E-commerce digital product platform 10% flat fee on...
Source: www.thinkific.com
Top 11 Thinkific Alternatives for Online course Creators in 2023
Teachable is one of the best Thinkific Alternatives. Teachable is one of the best and most available online teaching platforms which is widely known. The interface makes you feel very similar to Thinkific but gives better features than Thinkific. This platform is mainly useful for beginners who have a little bit of knowledge of coding.
Source: postforsuccess.com
Top 11 Best Kajabi Alternatives To Sell Online Course In 2023
Teachable enables you to connect your existing website with Teachable using a custom domain if you already have one. In addition, Teachable allows you to build a brand-new website or landing page. By enabling you to make multimedia lectures and movies, it also broadens the functions it offers.
Source: www.techblitz.org

NumPy Reviews

25 Python Frameworks to Master
SciPy provides a collection of algorithms and functions built on top of the NumPy. It helps to perform common scientific and engineering tasks such as optimization, signal processing, integration, linear algebra, and more.
Source: kinsta.com
Top 8 Image-Processing Python Libraries Used in Machine Learning
Scipy is used for mathematical and scientific computations but can also perform multi-dimensional image processing using the submodule scipy.ndimage. It provides functions to operate on n-dimensional Numpy arrays and at the end of the day images are just that.
Source: neptune.ai
Top Python Libraries For Image Processing In 2021
Numpy It is an open-source python library that is used for numerical analysis. It contains a matrix and multi-dimensional arrays as data structures. But NumPy can also use for image processing tasks such as image cropping, manipulating pixels, and masking of pixel values.
Source: www.analyticsvidhya.com
4 open source alternatives to MATLAB
NumPy is the main package for scientific computing with Python (as its name suggests). It can process N-dimensional arrays, complex matrix transforms, linear algebra, Fourier transforms, and can act as a gateway for C and C++ integration. It's been used in the world of game and film visual effect development, and is the fundamental data-array structure for the SciPy Stack,...
Source: opensource.com

Social recommendations and mentions

Based on our record, NumPy seems to be more popular. It has been mentiond 119 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Teachable mentions (0)

We have not tracked any mentions of Teachable yet. Tracking of Teachable recommendations started around Mar 2021.

NumPy mentions (119)

  • Building an AI-powered Financial Data Analyzer with NodeJS, Python, SvelteKit, and TailwindCSS - Part 0
    The AI Service will be built using aiohttp (asynchronous Python web server) and integrates PyTorch, Hugging Face Transformers, numpy, pandas, and scikit-learn for financial data analysis. - Source: dev.to / 4 months ago
  • F1 FollowLine + HSV filter + PID Controller
    This library provides functions for working in domain of linear algebra, fourier transform, matrices and arrays. - Source: dev.to / 8 months ago
  • Intro to Ray on GKE
    The Python Library components of Ray could be considered analogous to solutions like numpy, scipy, and pandas (which is most analogous to the Ray Data library specifically). As a framework and distributed computing solution, Ray could be used in place of a tool like Apache Spark or Python Dask. It’s also worthwhile to note that Ray Clusters can be used as a distributed computing solution within Kubernetes, as... - Source: dev.to / 8 months ago
  • Streamlit 101: The fundamentals of a Python data app
    It's compatible with a wide range of data libraries, including Pandas, NumPy, and Altair. Streamlit integrates with all the latest tools in generative AI, such as any LLM, vector database, or various AI frameworks like LangChain, LlamaIndex, or Weights & Biases. Streamlit’s chat elements make it especially easy to interact with AI so you can build chatbots that “talk to your data.”. - Source: dev.to / 9 months ago
  • A simple way to extract all detected objects from image and save them as separate images using YOLOv8.2 and OpenCV
    The OpenCV image is a regular NumPy array. You can see it shape:. - Source: dev.to / 9 months ago
View more

What are some alternatives?

When comparing Teachable and NumPy, you can also consider the following products

PowerSchool - PowerSchool provides a K-12 education technology platform for operations, classroom, student growth, and family engagement.

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

Clever - syncing between education applications for K-12 schools

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

Claroline - Claroline is a collaborative eLearning and eWorking platform.

OpenCV - OpenCV is the world's biggest computer vision library

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