Skip to main content

Blog entry by Ali Haider Shalwani

Data Science Toolkit: Progress in the World of Data with Leading Resources

Data Science Toolkit: Progress in the World of Data with Leading Resources

The best data science toolkit to help you succeed. Find leading blogs, podcasts, YouTube channels, project ideas, and numerous other data science resources in one place.


100s of 1000s of people are everyday planning to get started with their data science journey while most of them are actively & continuously looking out for data science resources & sites, to begin with. With tons of resources & sites available, one might wonder where to get the most useful & up-to-date data science material.  

And, if you are one of those, then you have landed on the correct page because I have curated a list of resources that have helped me a lot with learning data science & should probably help you out too.


Data Science Blogs


Data Science Blogs to Follow

Being a data scientist, you would want to stay updated with the recent happenings in data science, machine learning, and artificial intelligence. There are some quality blogs producing engaging and interesting content day in day out. These blogs can also be regarded as excellent data science resources. 

1. KDnuggets: It has always been on the top of my list; they provide new blogs on data science, machine learning, artificial intelligence, and analytics on a routine basis. So, if you need a new data science blog frequently or on daily basis then KDnuggets is your option to go with.

Link to site: https://www.kdnuggets.com/

2. Data Science Central: From data science cheat sheets to PDFs to infographics, you can find all the useful material here with just one search.

Link to site: https://www.datasciencecentral.com/  

3. Towards Data Science: With towards data science, you can clarify your data science, ML, and AI basics & fundamentals. Additionally, they provide a wide range of blogs on statistics & mathematics that can further aid your learning journey.

Link to site: https://towardsdatascience.com/  

4. Data Science Dojo: From big data to data analytics to statistics, Data Science Dojo is providing some useful blogs on several different areas of data science. Though, the blogs are limited in number but are highly recommended for all those who are just getting started with data science.

Link to site: https://online.datasciencedojo.com/blogs/  

5. R bloggers: undoubtedly, you can find some most amazing blogs on R, Python, regression, and statistics here. Hence, if you are looking for clarity in any of the aforementioned areas, then R bloggers is your way to go.

Link to site: https://www.r-bloggers.com/


For more data science articles, check out this blog.


Data Science Communities


Data Science Communities

Online forums and communities can be a really interactive way of learning data science. With a number of enthusiasts all over the world, these online spaces can serve as a resource for staying on track and updated, being a valuable contribution to your data science toolkit. 

1. Kaggle: One of the most useful online communities for data scientists & practitioners; with Kaggle you can learn some of the most essential Python, machine learning, and data science concepts.

Link to site: https://www.kaggle.com/

2. Reddit: This online community can help you find some helpful data science articles on a routine basis, which can enhance your knowledge & understanding.

Link to site: https://www.reddit.com/r/datascience/  

3. Stack Overflow: If you are currently in the learning phase, then it is one of the most useful online community for you to find the answers to your questions.

Link to site: https://stackoverflow.com/

4. Mathematics Stack Exchange: Need help with mathematics? Then this mathematics forum can help you with it at any level. You can easily find answers to your math-related queries here.

Link to site: https://math.stackexchange.com/


Data Science YouTube Channels


Data Science YouTube Channel

There are a number of YouTube channels sharing the concepts of data science. You, obviously, will not be able to go through all the videos. Here are some of the best data science resources when it comes to YouTube. 

1. Ken Jee: Following his channel can make it a lot easier for you to break into the field of data science. Ken Jee shares his own learning experience & makes some useful career-related suggestions.

Link to channel: https://www.youtube.com/results?search_query=ken+jee 

2. Data Professor: Learn about data science,
machine learning, bioinformatics, research, and teaching with these amazing
videos & content produced by data professor. 

Link to channel: https://www.youtube.com/results?search_query=data+professor

3. Data Science Dojo: Are you new to the field of data science? Then Data Science Dojo can help you with learning some of the most significant concepts of machine learning, artificial intelligence, Python programming, and R programming.

Link to channel: https://www.youtube.com/results?search_query=data+science+dojo  

Check out their Data Science Bootcamp now, to begin with, your career. 

4. Krish Naik: To get the know-how of how data science, machine learning, deep learning, and artificial intelligence work in a real-life scenario, follow his amazing tutorials & content.

Link to channel: https://www.youtube.com/results?search_query=krish+naik 

5. Code Basics: Start learning programming in the easiest & untaught manner. So, if you are looking for a veracious channel to learn to program, then Code Basics is your channel to trust on. 

Link to channel: https://www.youtube.com/results?search_query=code+basic


For more Data Science YouTube Channels, check out this blog post.


Data Science Podcasts


Data Science Podcasts

Podcasts are an excellent way of staying updated in the world of data science. I have listed a few useful data science podcasts on Sound-Cloud, Apple Podcast, and Spotify to help you learn and make the most out of your time.

1. Spotify

A. Data Skeptic: These podcasts from data skeptic will bring amazing tutorials on statistics, machine learning, big data, and data science. Start learning now with them.

Link to Podcast: https://open.spotify.com/show/1BZN7H3ikovSejhwQTzNm4

B. SuperDataScience: With SuperDataScience you can boom your analytics career. It includes podcasts on statistics, R, Python, SQL programming, tableau, machine learning, Hadoop, databases, and other analytical tools.

Link to Podcast: https://open.spotify.com/show/1n8P7ZSgfVLVJ3GegxPat1

2. Apple Podcast

A. Women in Data Science: Hear from women leaders across the data science profession, their advice on data science & lessons that can help you build your career.

Link to Podcast: https://podcasts.apple.com/us/podcast/women-in-data-science/id1440076586

B. Data Science in Production: This podcast primarily focuses on the tools & techniques that can help you put your models into production faster.

Link to Podcast: https://podcasts.apple.com/us/podcast/data-science-in-production/id1455613667

3. Sound Cloud

A. Data Hack Radio: This series of Podcast features Kunal Jain from Analytics Vidhya along with top data science leaders & practitioners.

Link to Podcast: https://soundcloud.com/datahack-radio

B. O’Reilly Data Show Podcast: With these podcasts, you can explore the opportunities that are driving the field of data science & big data.

Link to Podcast: https://soundcloud.com/oreilly-radar/sets/the-oreilly-data-show-podcast


For more podcasts, check out this blog.

Data Science Movies to Watch


Data Science Movies

The world of data science is not just about writing code and building models. Data science has a lot of influence, both directly and indirectly, on the entertainment industry. In fact, movies and tv shows can be used as one of the data science resources by aspiring scientists and engineers. When you need to freshen up or take a break from tough problems, these movies can be of great help. 

1. Minority Report (2002): An action-thriller directed by Steven Spielberg, starring Tom Cruise. We have generally seen data being used to infer new information, but here the data is being used to predict crime predisposition.  

2. Interstellar (2014): Christopher Nolan’s cinematic success won an Oscar for best visual effects and grossed over $677 million worldwide. The movie includes quadrilateral robots like TARS & CASE that are true examples of the that we have made within the AI domain.  

3. The Imitation Game (2014): The move is based on the real-life story of Alan Turing & also describes the process of creating the first-ever machine within the field of cybersecurity & cryptography.  

4. The Queen’s Gambit (2020): One of the most popular Netflix series, with over 62 million viewers, tells the story of Beth Harmon; a made-up chess star who beats all odds in life from being orphaned as a child to battling drug addiction & chess competitions. Though the series is not really related to data science, but how Beth mentally plays the game by visualizing the chessboard on the ceiling is much like how an AI system works. For the past few years, AI researchers are trying to build a computer-generated bot version of Beth.


For more AI, ML, and data science-related movies, check out the blog here.

Top Data Science Books


Top Data Science Books

Books are one of the best additions to any individual's data science toolkit. There is an immense amount of literature out there, helping aspiring data scientists clarify some concepts and acquire valuable information. 

1. An Introduction to Statistical Learning- With Applications in R: This book provides an overview of the field of statistical learning, which covers essential tools that can help in handling vast data sets varying from biology to marketing to finance.  

2. The Hundred-Page Machine Learning Book: This book covers a wide range of topics in just 100 pages. Some of machine learning’s core concepts are explained here in just a few words.  

3. The Cartoon Guide to Statistics: By using cartoons & humor, the author explains some of the essential statistical concepts that one might find difficult to comprehend. This book is highly recommended if you are just getting started with data science & statistics.  

4. Forecasting- Principles & Practice: Making decisions based on the future forecasts is required at several instances, for example, whether to build up a new power plant in the next five years or not? Such decisions can only be based on forecasts. This book can assist you with understanding the basics & principles of forecasting.


For more data science books, check out this blog.

Data Science Newsletters


Data Science Newsletter

Similar to blogs and podcasts, Newsletters can be a valuable addition to your data science toolkit. You’ll get curated articles at regular intervals to stay on top of things. 

1. Mode Analytics: This collaborative platform combines SQL, Python, and R together in one place. You can subscribe to amazing data science-related newsletters with mode. 

Link to site: https://mode.com/  

2. Data Science Weekly: You can find curated articles here for data science news, jobs, and blogs for free. So, if you are looking for routine data science stuff, then data science weekly is your way to go with.  

3. Data Science Dojo: They provide
a weekly newsletter on a wide array of topics including data, programming, AI,
infrastructure, Ops, data science, and ML. With them, you are subscribing to
blogs & articles that are relevant to you & your learning. 

Link to site: https://datasciencedojo.com/newsletter/

4. Data Elixir: A weekly dose for you all the top data science picks, covering machine learning, data visualization, analytics, and strategy. Stay up to date in data science with them.  

Link to site: https://dataelixir.com/

Data Science Datasets


Data Science Datasets

If you want to test and polish your newfound skills, the following valuable datasets can serve as one of the best data science resources. 

1. Kaggle Datasets: These datasets can help you with exploring, sharing, and analyzing quality data.  

Find the datasets here: https://www.kaggle.com/datasets  

2. Data Market: You can find 100-million-time series from UN, World Bank, Eurostat, and other important data providers, which can ultimately help you with visualizing world economies & societies.  

3. Datacatalogs.org: It includes a comprehensive list of data portals from around the world i.e. Canada, United States, EU, and more.  

Find the dataset here: http://datacatalogs.org/  

4. NASDAQ Data Store: With NASDAQ, you can access all the market & stock data.  

5. Data Science Dojo: You can find a wide range of datasets here, including, consensus income, Dow Jones Index, car evaluation, real estate evaluation, and more.  

Find the dataset here: https://code.datasciencedojo.com/tshrivas/dojoHub


For more datasets, check out this blog post.


Top Data Science LinkedIn pages to follow


Top Data Science LinkedIn Pages

LinkedIn can serve as another top data science resource, particularly if you’re looking to read short, engaging articles and get inspired by the stories of individuals. The pages listed below are worth following. 

1. Machine Learning Mastery: You can find some useful machine learning articles & resources here that can help you to get started with applied ML. So, if you are into ML then Machine Learning Mastery is your place, to begin with. 

2. Towards AI: With having 1800+ contributing writers from university professors to industry experts, they have a wide range of articles on tech, science, mathematics, engineering, and the future. If you are looking for some high-quality articles, then start scrolling through them.  

3. Machine Learning India: Looking for useful infographics & PDFs? Then start following Machine Learning India because they have a ton of useful infographics, data science PDFs, and cheat sheets.  

4. Data Science Dojo: Are you new to data science? Do you need daily content? Then I highly recommend you to start following Data Science Dojo. They share useful data science resources; be it an infographic, a cheat sheet, a blog, or a joke for humor. It doesn’t really matter if you are a beginner or an expert in the field, they have the right mix of content for everyone. Adding on, their weekly polls can help you test your data science skills, while their frequently held online webinars can help you with enhancing your knowledge.  

5. Data Science Central: Similar to their blog, they have amazing data science articles on their LinkedIn profile as well. If you are a LinkedIn Freak, then you should start following their page now.


Data Science Free Tools


Data Science Free Tools

A data science toolkit devoid of tools and software is not really a toolkit, to be fair. There are some quality tools out there, including open-source software, that a data scientist can benefit from. Here are the best data science resources in the realm of software applications. 

1. TensorFlow: It is a free & open-source software library for machine learning. TensorFlow is commonly used for neural networks, though, it can be used for a wide range of tasks.  

Link to site: https://www.tensorflow.org/  

2. Anaconda: It is used for the scientific computing of Python & R programming languages, which helps in package management & deployment. The distribution includes data science packages for Windows, Linux, and macOS.  

Link to site: https://www.anaconda.com/  

3. GitHub: One of the largest & most developed platforms in the world, where millions of companies & developers build & maintain their software on.  

Link to site: https://github.com/  

4. Good Colab: This amazing product of google allows anyone to write & execute random Python code through the browser. Generally, it is a good fit for machine learning, data analysis, and education. Additionally, colab is a hosted Jupyter notebook that requires no setup & provides free access to computing resources.  

Link to site: https://colab.research.google.com/notebooks/


Data Science Projects


Data Science Projects

The world of data science is nothing without practical experience and real-world projects. In your data science toolkit, therefore, you should have some quality projects. This will not only help you gain valuable experience but also strengthen your portfolio. 

 1. Beginner Level 

A. Fake News Detection: If you are new to data science then this project can assist you to level up your data science career. Using Python, you can detect false & misleading news across social media & online channels.  

B. Forest Fire Prediction: Using K-means clustering one can identify the hotspots of forest fires & severity, which can help in lessening & controlling the ecosystem damage.  

C. Twitter Sentiment Analysis: One of the widely used text mining techniques, this project includes sentiment analysis of the text (tweets) in form of positive, negative, and neutral.

2. Intermediate Level 

A. Recognition of Speech Emotion: Willing to learn on the usage of different libraries? Then you must go with this project idea. With different editor tools, you can tell how the speech emotion is appearing. This program model can be built as a data science project.  

B. Gender & Age Detection with Data Science: This type of real-time project can help you grab the recruiter’s attention during an interview. Additionally, with this project, you can also learn convolutional neural networks.  

C. Chatbots: One of the highly demanded & crucial elements for all businesses these days. Thereby, working on this data science project can help you uplift your career.

3. Advance-level 

A. Credit Card Fraud Detection: Once you are through practicing the beginner & intermediate level of projects, you can move to this level. With the Credit Card Fraud Detection project, you can learn about how to use R with different algorithms like decision trees & logistic regression. 

B. Traffic Sign Recognition: The purpose of this project is to achieve a higher level of accuracy in self-driving car technologies using CNN techniques, which can help in identifying different types of traffic signals by the input of an image.  

C. Customer Segmentations: One of the most popular & important data science projects that can help marketers to reach the targeted & relevant group of people via marketing activities. Methods of clustering can play a vital role here that can assist in dividing the audience within age brackets, income, gender, and interest.


For more data science project ideas, check out this blog.

Conclusion

Whether you are a beginner or an expert in the field of data science, this comprehensive data science toolkit can be your ultimate support at all career levels. Bookmark this post for future assistance & use.


Add value to your data science skillset with our Python for Data Science training.  


  • Share