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Python for Data Science with Assignments

A Comprehensive and Practical Hands-On Guide to Learning Python for Beginners, Aspiring Developers, Self-Learners, etc.

Rating ⭐️: 4.7 out 5
Students 👨‍🎓 : 18046
Duration ⏰ : 9.5 hours on-demand video
Created by 👨‍🏫: Meritshot Academy

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⚠️ Its free for first 1000 enrollments only!


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Practical Deep Learning For Coders

This 7-week course is designed for anyone with at least a year of coding experience, and some memory of high-school math. You will start with step onelearning how to get a GPU server online suitable for deep learningand go all the way through to creating state of the art, highly practical, models for computer vision, natural language processing, and recommendation systems.

🆓 Free Online Course
Rating⭐️: 4.1 out 5
Duration ⏰: 7 weeks
💻 Lecture Videos
🏃‍♂️ Self paced
Teacher 👨‍🏫 : Prof. Jeremy Howard

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#programming #deeplearning
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How To Use R Programming for Research

Use R Programming for Scientific Research

Rating ⭐️: 4.5 out 5
Students 👨‍🎓 : 19,897
Duration ⏰ : 1.5 hours on-demand video
👩‍💻 2 coding exercises
⬇️ 29 downloadable resources
Created by 👨‍🏫: Prof Asad Rasul

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⚠️ Its free for first 1000 enrollments only!


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10 Best Practices for Data Science

The main bottleneck in data science are no longer compute power or sophisticated algorithms, but craftsmanship, communication, and process.

And that the aim is to not only produce work that is accurate and correct, but also can be understood, work that others can collaborate on.

Rule 1: Start Organized, Stay Organized
Rule 2: Everything Comes from Somewhere, and the Raw Data is Immutable
Rule 3: Version Control is Basic Professionalism
Rule 4: Notebooks are for Exploration, Source Files are for Repetition
Rule 5: Tests and Sanity Checks Prevent Catastrophes
Rule 6: Fail Loudly, Fail Quickly
Rule 7: Project Runs are Fully Automated from Raw Data to Final Outputs
Rule 8: Important Parameters are Extracted and Centralized
Rule 9: Project Runs are Verbose by Default and Result in Tangible Artifacts
Rule 10: Start with the Simplest Possible End-to-End Pipeline
Lessons

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Data Science Projects

Collection of data science projects in Python

Creator: Vaibhav Singh
Stars ⭐️: 1.5k
Forked By: 406
https://github.com/veb-101/Data-Science-Projects

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Become a Citizen Data Scientist with HyperSense-AI Studio

Use R Programming for Scientific Research

Rating ⭐️: 4.6 out 5
Students 👨‍🎓 : 3139
Duration ⏰ : 1.5 hours on-demand video
Created by 👨‍🏫: Learning Hypersense

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Data Science BootCamp - From Analysing Data To Creating ML Models

This free Data Science Bootcamp will help you get started on the roadmap towards a career as top Data Scientist. Master the basics of Python, Tableau, ML, AI and more.


✅ Free Online Course
🏃‍♂️ Self paced
Duration ⏰ : 6 weeks long
Source: geeksforgeeks

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DATA SCIENCE :THEORIES , MODELS , ALGORITHMS , AND ANALYTICS

by S A N J I V R A N J A N D A S


📄 462 pages

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Data Science Full Course 2024 | Data Science Course For Beginners | Learn Data Science |

This Data Science Course 2024 covers all the important skill sets required to get you a job as a Data Scientist!

This particular Data Science Course For Beginners has been taught by our top industry experts associated with companies like Google, Meta, and Microsoft. So, stay until the end of this video, you will understand Data Science from Fundamentals To Solving Basic Data Science Problems Using Machine Learning Algorithms.

With this Data Science Course 2024, we will give you the Fundamental idea of what is data science, What Datasets are all about, Basic Machine Learning Algorithms, and how you can solve real-world problems like heart disease detection using Data science.

We will also help you with the trending project idea which is creating a Chatbot of your own like ChatGPT using data science. We will also highlight some of the important data science interview questions.


✅ Free Online Course
🏃‍♂️ Self paced
Duration ⏰ : 11-12 hours long
Source: Intellipaat

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Learning Data Science: Understanding the Basics

Many of the people who work on data science teams won't be data scientists. They'll be the managers and associates who want to gain real business value from your organization's data. These team members need to understand the language of data science so they can ask better questions, understand processes, and help effectively lead their teams and organizations to making better data-driven decisions. This course is an introduction to data science for people who aren't planning on being full-time data scientists. It introduces big data concepts, tools, and techniques, including gathering and sorting data, working with databases, understanding structured and unstructured data types, and applying statistical analysis. Business coach and author Doug Rose helps you speak the language of data science so that you can guide your organization through the opportunities and limitations in this dramatically growing field.


✅ Free Online Course
🏃‍♂️ Self paced
Duration ⏰ : 1-2 hours long
4 quizzes
Source: linkedin learning

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8 Great Data Science Books For Beginners

In the past few years public interest in data science has surged. What had been a fairly esoteric field is now a common topic in the news, in politics and international law, and in our social media feeds. Data literacy is becoming a highly desired skill in every industry, and consumers enter data points into massive business intelligence systems every day. Whether you just want to stay informed in the data craze or you’re looking to kickstart your data science or data literacy journey, this article features a list of books that can help newcomers navigate the world of data science.

1. “The Data Science Handbook
2. “Doing Data Science: Straight Talk from the Frontline” by Cathy O'Neil and Rachel Schutt
3. “Numsense! Data Science for the Layman: No Math Added” by Annalyn Ng and Kenneth Soo
4. “The Art of Data Science” by Roger D. Peng and Elizabeth Matsui
5. “Data Science For Dummies” by Lillian Pierson
6. “Big Data For Dummies” by Judith Hurwitz, Alan Nugent, Fern Halper, and Marcia Kaufman
7. “Data Jujitsu: The Art of Turning Data into Product” by DJ Patil
8. “Big Data: A Revolution That Will Transform How We Live, Work, and Think” by Viktor Mayer-Schönberger and Kenneth Cukier

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