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Django with Data Science

Django Ninjas

Create professional and nicely looking User Interface in Django for Data Science with the use of Semantic UI framework. Understand the core concepts behind Pandas, Numpy, Matplotlib & Seaborn in order to create custom analytic tool i the browser for people who don't know anything about programming. This unique course will introduce new concepts step by step and at the end the Student will have a very interesting position in the portfolio.

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Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
This course emphasizes user interface design for data science, catering to individuals with no programming experience
The focus on Pandas, Numpy, Matplotlib, and Seaborn empowers learners to create custom analytics tools for non-programmers
This unique course introduces concepts gradually, enabling students to build a strong foundation in data analytics
The use of the Semantic UI framework ensures the creation of professional and visually appealing user interfaces

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Reviews summary

Django with data science: web interface for analytics

According to students, this course offers a solid entry point for anyone looking to bridge Django web development with data science concepts. Learners praise the practical hands-on projects and the instructor's clear, well-structured explanations, which are particularly helpful for building a portfolio-ready analytic tool. However, some reviewers note that the code examples can be outdated, leading to compatibility issues and debugging challenges. The data science coverage is generally basic, focusing more on presentation than advanced techniques, which might be a warning for experienced data scientists seeking depth.
The pace is good for some, but prior experience affects perception of speed.
"The pace was just right for someone with intermediate Python skills."
"Sometimes, the code examples felt a bit rushed, and I had to pause frequently."
"While it's a good starting point, those with prior Django experience might find some parts too slow..."
Instructor is often praised for clear explanations and structured material.
"The instructor explains complex concepts clearly, especially on how to integrate Pandas and Matplotlib visualizations directly into Django templates."
"The instructor's voice is clear, and the explanations are thorough. The projects really cemented the learning."
"The instructor clearly structured the material, making it easy to follow even for someone new to Django."
Effectively bridges Django web development with data science concepts.
"This course is a goldmine for anyone looking to bridge Django with Data Science... I loved the hands-on projects; they were practical and immediately applicable."
"As a web developer wanting to get into data science applications, this course provided the perfect entry point. The step-by-step guidance on creating a Django UI for data analysis was invaluable."
"I found this course very helpful for understanding how to deploy data science models with a web interface using Django. The practical examples were key."
Provides a good introduction but lacks depth for advanced data science topics.
"My main feedback is that it could go deeper into advanced data science techniques or more complex Django deployments."
"The data science aspects were very basic; I didn't expect to learn advanced machine learning here. It's more about presenting data."
"While it's a good starting point, those with prior Django experience might find some parts too slow, and data scientists might find the ML concepts too shallow."
Several reviewers reported issues with outdated code and library versions.
"Completely outdated! Many dependencies failed to install or run due to version mismatches. It was incredibly frustrating trying to get the code to work."
"Some of the code felt a bit outdated, especially with newer versions of Django and Python. I struggled with debugging some errors that weren't covered."
"The content covers the basics well enough, but it does show its age. Some libraries used are not the latest versions, which caused minor compatibility issues."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Django with Data Science with these activities:
Read 'Data Science for Business'
Gain a comprehensive understanding of the role of data science in business decision-making and strategy.
View Data Science for Business: What You Need to... on Amazon
Show steps
  • Purchase or borrow the book
  • Read the book, taking notes and highlighting important concepts
Review Linear Algebra and Statistics Concepts
Ensure a strong foundation in linear algebra and statistics, which are essential for understanding data science models and algorithms.
Show steps
  • Review notes or textbooks on linear algebra and statistics
  • Complete practice problems and exercises
Learn the Basics of Data Science and AI
Start the course with a solid base in data science, AI, and machine learning to enhance your learning experience.
Show steps
  • Enroll in an online course or tutorial on Data Science and AI
  • Complete all the modules and assignments
Eight other activities
Expand to see all activities and additional details
Show all 11 activities
Solve Coding Challenges and Practice Data Analysis
Sharpen your programming and data analysis skills through regular practice, improving your confidence and problem-solving abilities.
Browse courses on Skill Development
Show steps
  • Sign up for a coding challenge platform or use online data analysis tools
  • Solve coding challenges and practice data analysis tasks on a regular basis
Follow Online Tutorials
Following well-structured tutorials will provide you with step-by-step guidance on implementing various concepts and techniques covered in the course.
Browse courses on Django
Show steps
  • Identify tutorials that cover specific topics or skills you want to improve.
  • Follow the tutorials carefully, taking notes and experimenting with the code.
  • Apply what you've learned to your own projects.
Solve Practice Problems
Solving practice problems on these topics will strengthen your understanding of the core concepts and help you apply them effectively in your projects.
Browse courses on Pandas
Show steps
  • Identify relevant practice problems from online resources or textbooks.
  • Break down the problem into smaller steps.
  • Implement the solution using the appropriate libraries and techniques.
  • Test and debug your code.
  • Review and analyze your solutions to identify areas for improvement.
Join a Data Science Study Group
Connect with peers, share knowledge, and collaborate on projects to enhance your learning and understanding.
Show steps
  • Join a study group or create one with friends or classmates
  • Meet regularly to discuss course material, work on projects, and support each other
Create a Presentation or Infographic on Data Science Concepts
Deepen your understanding of data science concepts by creating visual aids that explain and illustrate them for yourself or others.
Show steps
  • Choose a data science concept to focus on
  • Gather information and research the concept thoroughly
  • Create a presentation or infographic that visually explains the concept
Build a Data Visualization Tool
Creating a data visualization tool will allow you to apply your knowledge of libraries like Matplotlib and Seaborn to create visually appealing and informative representations of data.
Browse courses on Data Visualization
Show steps
  • Define the purpose and scope of your visualization tool.
  • Gather and prepare your data.
  • Choose appropriate visualization techniques and libraries.
  • Create a user interface for interacting with the tool.
  • Deploy and share your tool.
Contribute to Open-Source Data Science Projects
Gain practical experience and contribute to the data science community by participating in open-source projects and collaborating with others.
Browse courses on Community Involvement
Show steps
  • Identify open-source data science projects that align with your interests
  • Join the project community and contribute to code, documentation, or testing
Mentor Junior Data Scientists or Students
Consolidate your knowledge by sharing it with others, reinforcing your understanding and contributing to the growth of the data science community.
Show steps
  • Volunteer as a mentor at a local coding bootcamp or university
  • Provide guidance and support to junior data scientists or students

Career center

Learners who complete Django with Data Science will develop knowledge and skills that may be useful to these careers:
Data Analyst
Data Analysts apply mathematical and statistical techniques to analyze data and interpret results in order to help businesses understand trends and make better decisions. This course in Django with Data Science will be extremely useful for someone seeking this career, as it will help build a foundation understanding of data science, including how to analyze data, interpret results and create meaningful visualizations. These are all important skills that an aspiring Data Analyst will need to be successful in their role.
See salaries and explore the career path for Data Analyst
Data Scientist
Data Scientists use programming, statistics, and machine learning techniques to extract insights from data. This course in Django with Data Science may be useful to someone looking to pursue this career path, as it will provide a foundation for understanding data science concepts and applications. Additionally, the course's focus on using Python and Django can be beneficial for building web applications that incorporate data analysis and visualization.
See salaries and explore the career path for Data Scientist
Software Engineer
Software Engineers design, develop, and test software applications. This course in Django with Data Science may be useful to someone seeking a career in this field, as it will provide a foundation for understanding software development and data analysis. In particular, the course's focus on using Python and Django can be beneficial for building web applications that integrate data analysis and visualization.
See salaries and explore the career path for Software Engineer
Web Developer
Web Developers create and maintain websites and web applications. This course in Django with Data Science may be useful to someone seeking this career path, as it will provide a foundation for understanding web development and data science. In particular, the course's focus on using Python and Django can be beneficial for building web applications that incorporate data analysis and visualization.
See salaries and explore the career path for Web Developer
Business Analyst
Business Analysts analyze data and business processes to identify problems and opportunities. This course in Django with Data Science may be useful to someone seeking this career path, as it will provide a foundation for understanding data analysis and business processes. In particular, the course's focus on using Python and Django can be beneficial for building web applications that incorporate data analysis and visualization.
See salaries and explore the career path for Business Analyst
Statistician
Statisticians collect, analyze, interpret, and present data to help businesses and organizations make informed decisions. This course in Django with Data Science may be useful to someone seeking this career path, as it will provide a foundation for understanding data analysis and statistics. In particular, the course's focus on using Python and Django can be beneficial for building web applications that incorporate data analysis and visualization.
See salaries and explore the career path for Statistician
Financial Analyst
Financial Analysts analyze financial data to help businesses make investment decisions. This course in Django with Data Science may be useful to someone seeking this career path, as it will provide a foundation for understanding data analysis and financial markets. In particular, the course's focus on using Python and Django can be beneficial for building web applications that incorporate data analysis and visualization.
See salaries and explore the career path for Financial Analyst
Market Researcher
Market Researchers gather and analyze data to understand customer needs and market trends. This course in Django with Data Science may be useful to someone seeking this career path, as it will provide a foundation for understanding data analysis and market research. In particular, the course's focus on using Python and Django can be beneficial for building web applications that incorporate data analysis and visualization.
See salaries and explore the career path for Market Researcher
Data Engineer
Data Engineers build and maintain the infrastructure and systems that store and process data. This course in Django with Data Science may be useful to someone seeking this career path, as it will provide a foundation for understanding data engineering and data science. In particular, the course's focus on using Python and Django can be beneficial for building web applications that incorporate data analysis and visualization.
See salaries and explore the career path for Data Engineer
Machine Learning Engineer
Machine Learning Engineers develop and implement machine learning models to solve business problems. This course in Django with Data Science may be useful to someone seeking this career path, as it will provide a foundation for understanding data science and machine learning. In particular, the course's focus on using Python and Django can be beneficial for building web applications that incorporate data analysis and visualization.
See salaries and explore the career path for Machine Learning Engineer
Actuary
Actuaries analyze risk and uncertainty to help businesses and individuals make informed decisions. This course in Django with Data Science may be useful to someone seeking this career path, as it will provide a foundation for understanding data analysis and risk management. In particular, the course's focus on using Python and Django can be beneficial for building web applications that incorporate data analysis and visualization.
See salaries and explore the career path for Actuary
Quantitative Analyst
Quantitative Analysts use mathematical and statistical techniques to analyze financial data and make investment decisions. This course in Django with Data Science may be useful to someone seeking this career path, as it will provide a foundation for understanding data analysis and financial markets. In particular, the course's focus on using Python and Django can be beneficial for building web applications that incorporate data analysis and visualization.
See salaries and explore the career path for Quantitative Analyst
Data Visualization Specialist
Data Visualization Specialists create visual representations of data to help businesses and individuals understand trends and make better decisions. This course in Django with Data Science may be useful to someone seeking this career path, as it will provide a foundation for understanding data science and data visualization. In particular, the course's focus on using Python and Django can be beneficial for building web applications that incorporate data analysis and visualization.
See salaries and explore the career path for Data Visualization Specialist
Business Intelligence Analyst
Business Intelligence Analysts collect, analyze, and interpret data to help businesses make informed decisions. This course in Django with Data Science may be useful to someone seeking this career path, as it will provide a foundation for understanding data analysis and business intelligence. In particular, the course's focus on using Python and Django can be beneficial for building web applications that incorporate data analysis and visualization.
See salaries and explore the career path for Business Intelligence Analyst
Data Journalist
Data Journalists use data to tell stories and report on news events. This course in Django with Data Science may be useful to someone seeking this career path, as it will provide a foundation for understanding data science and journalism. In particular, the course's focus on using Python and Django can be beneficial for building web applications that incorporate data analysis and visualization.
See salaries and explore the career path for Data Journalist

Reading list

We've selected 12 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Django with Data Science.
Cover image
Python Data Science Handbook
Save
Provides a comprehensive introduction to Python data science, covering topics from basic data manipulation to advanced machine learning techniques. It valuable resource for both beginners and experienced data scientists.
Python Data Science Handbook: Essential Tools for...
Paperback
$$$
Machine Learning Con Pytorch Y Scikit Lean
Save
Provides a comprehensive introduction to machine learning with Python. It covers the basics of machine learning, as well as advanced topics such as deep learning and reinforcement learning. It valuable resource for both beginners and experienced data scientists.
(Español) Machine Learning con PyTorch y Scikit-Learn:...
Paperback
$$$
Cover image
Hands-On Machine Learning with Scikit-Learn, Keras,...
Save
Provides a practical introduction to machine learning with Python, using popular libraries such as Scikit-Learn, Keras, and TensorFlow. It great choice for beginners and intermediate learners looking to build their skills in machine learning.
Hands-On Machine Learning with Scikit-Learn, Keras,...
Paperback
$$
Hands-On Machine Learning with Scikit-Learn, Keras,...
Paperback
$$$
Hands-On Machine Learning with Scikit-Learn, Keras,...
Kindle Edition
$$
Cover image
Deep Learning with Python, Second Edition
Save
Provides a comprehensive introduction to deep learning with Python. It covers the basics of deep learning, as well as advanced topics such as convolutional neural networks and recurrent neural networks. It valuable resource for both beginners and experienced deep learning practitioners.
Deep Learning with Python, Second Edition
Paperback
$$
Deep Learning with Python, Second Edition
Kindle Edition
$$
Cover image
Deep Learning
Save
Provides a comprehensive introduction to deep learning. It covers the basics of deep learning, as well as advanced topics such as convolutional neural networks and recurrent neural networks. It valuable resource for both beginners and experienced deep learning practitioners.
Deep Learning
Paperback
$$$
Deep Learning (Adaptive Computation and Machine...
Hardcover
$$$
Deep Learning (Adaptive Computation and Machine...
Kindle Edition
$$$
Cover image
Natural Language Processing with Python
Save
Provides a comprehensive introduction to natural language processing with Python. It covers the basics of natural language processing, as well as advanced topics such as machine translation and text classification. It valuable resource for both beginners and experienced natural language processing practitioners.
Natural Language Processing with Python: Analyzing...
Paperback
$$$
Natural Language Processing with Python: Analyzing...
Kindle Edition
$$
Cover image
Data Science from Scratch
Save
Provides a practical introduction to data science from the ground up. It covers topics from data collection and cleaning to data visualization and modeling. It great choice for beginners looking to get started with data science.
Data Science from Scratch: First Principles with...
Paperback
$$
Data Science from Scratch: First Principles with...
Kindle Edition
$$
Data Science from Scratch: First Principles with...
Paperback
$$
Cover image
The Elements of Statistical Learning
Save
Provides a comprehensive introduction to statistical learning. It covers the basics of statistical learning, as well as advanced topics such as support vector machines and random forests. It valuable resource for both beginners and experienced data scientists.
The Elements of Statistical Learning: Data Mining,...
Hardcover
$$$
The Elements of Statistical Learning: Data Mining,...
Hardcover
$$$
The Elements of Statistical Learning: Data Mining,...
Kindle Edition
$$$
Cover image
Natural Language Processing with Python
Save
Provides a comprehensive introduction to speech recognition with Python. It covers the basics of speech recognition, as well as advanced topics such as automatic speech recognition and speaker recognition. It valuable resource for both beginners and experienced speech recognition practitioners.
Natural Language Processing with Python: Analyzing...
Paperback
$$$
(中文) Python Natural Language Processing(Chinese Edition)
Paperback
$$
Natural Language Processing with Python: Analyzing...
Kindle Edition
$$
Cover image
Reinforcement Learning, second edition
Save
Provides a comprehensive introduction to reinforcement learning with Python. It covers the basics of reinforcement learning, as well as advanced topics such as value iteration and policy iteration. It valuable resource for both beginners and experienced reinforcement learning practitioners.
Reinforcement Learning, second edition: An...
Hardcover
$$$
Reinforcement Learning, second edition: An...
Kindle Edition
$$$
Cover image
An Introduction to Statistical Learning
Save
Provides a gentle introduction to statistical learning. It covers the basics of statistical learning, as well as advanced topics such as Bayesian methods and ensemble methods. It great choice for beginners looking to get started with statistical learning.
An Introduction to Statistical Learning
Paperback
Check
An Introduction to Statistical Learning
Kindle Edition
Check
Cover image
Data Science for Business
Save
Provides a practical introduction to data science for business professionals. It covers topics from data collection and cleaning to data visualization and modeling. It great choice for beginners looking to get started with data science in a business context.
Data Science for Business: What You Need to Know...
Paperback
$$
Data Science for Business: What You Need to Know...
Kindle Edition
$$

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Time
7 hours
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Udemy
Instructor
Django Ninjas
Traffic lights
Read about what's good
what should give you pause
and possible dealbreakers
This course emphasizes user interface design for data science, catering to individuals with no programming experience
The focus on Pandas, Numpy, Matplotlib, and Seaborn empowers learners to create custom analytics tools for non-programmers
This unique course introduces concepts gradually, enabling students to build a strong foundation in data analytics
The use of the Semantic UI framework ensures the creation of professional and visually appealing user interfaces
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