Data Science tutorial for beginners | Projects
Last updated on Tue 17 Mar 2020
Learn Data Science from Beginner level to Advanced level. Know more about the projects that should be done at each level. There are mainly three levels.
Data science is, additionally known as data-driven science which is an interdisciplinary area approximately about scientific methods, processes, and structures to extract the data or insights from statistics in diverse forms, both based or unstructured, similar to data mining.
In choosing what to start with, the dataset has been divided into 3 levels:
1.) Beginner Level: The newbie degree comprises of knowledge sets that can be with no trouble labored with and doesn’t want any data set technique that is problematic in nature. They can be solved by utilizing normal regression/classification algorithms. You could get tutorials on these data science projects for beginners online.
2.) Intermediate level: The intermediate level has tougher data analytics initiatives which consist of mid and big data units that require excellent potential in pattern attention. Characteristic engineering can be of first-class aid here and there is not any limit on the usage of ML strategies as good.
3.) Advanced Level: The advanced degree is suitable for those who have to comprehend in evolved themes similar to deep studying, neural networks, recommender techniques and way more. This is when one wants to get creative; excessive dimensional information is featured here too...
Check it out Data Science Learning Objectives and Techniques
Beginner Level Data Science Projects:-
1. Iris Data Set
This is presumed to be the most versatile, resourceful and easy dataset in pattern recognition literature. Nothing else is easier than this data set in learning classification techniques and if you are just beginning data science then this is where you start from. Its data has only 150 rows and 4 columns.
2. Titanic Data Set
This is a very versatile dataset in having so many help guides and tutorials, in the global data science community. If you are serious about pursuing a career in data science, this project will give you more than enough of what you need.
3. Boston Housing Data Set
This data set is popularly used in pattern recognition literature and originates from the real estate industry in Boston, USA. Also a regression problem, its data has 506 rows and 14 columns.
It is a small data set giving you the opportunity to attempt any technique and not worrying about any memory issue on your computer.
4. Bigmart Sales Data Set
One industry known to extensively use analytics in optimizing business processes is retail. Various tasks such as inventory management, product placement, product building, customized offers, etc. are properly carried out using data science techniques.
Of course, as its name implies, it comprises of the transaction records of sales stores, which is a regression problem. The data comprises of 8523 rows and 12 variables.
5. Loan Prediction Data Set
Insurance, among all industries, is known to have the largest use data science methods and analytics. You are provided with enough information to work on data sets of insurance companies, the challenges to be faced, strategies to be used, the variables that would influence the outcome, and many others. It has a classification problem with 615 rows and 13 columns.
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Intermediate Level Data Science Projects:-
1. Million Song Data Set
You might not be aware of the fact analytics is used in the entertainment industry as well. It is a regression problem which consists 515345 observations and 90 variables. On the other hand, it is just a tiny subset of its million song data original database.
2. Black Friday Data Set
This particular dataset comprises of various sales transactions that are captured at a retail store. It is a classic data set to help you explore feature engineering skills you must have acquired and also daily understanding from the shopping experience. It is a regression problem having 550069 rows and 12 columns.
3. Movie Lens Data Set
Movie Lens DataSet gives you the opportunity to build a recommendation engine. If you aren’t aware, it is known to be the most popular and quoted data set in the data science industry. It comes in different dimensions and has over a million ratings from 6000 users on more than 4000 movies.
4. Trip History Data Set
Coming from a bike-sharing service in the US, it requires you to utilize your skills in pro data munging. It is a classification problem with each file having 7 columns and it is provided quarter-wise from 2010.
5. Census Income Data Set
Census Income DataSet is a classic machine learning problem and an imbalanced classification. Machine learning is known to be extensively used for solving imbalanced problems like fraud detection, cancer detection, etc. This dataset has 48842 rows and 14 columns.
6. Human Activity Recognition
This is taken via smartphones embedded with inertial sensors of 30 human subjects recordings. Several machine learning courses make use of this data for students to practice with it. It is more of a multi-classification problem having 10299 rows and 561 columns.
7. Text Mining Data Set
This data set is originally from siam competition 2007. The dataset comprises of aviation safety reports describing the problems which occurred in certain flights. It is a multi-classification, high dimensional problem. It has 21519 rows and 30438 columns.
Advanced Level Data Science Projects:-
1. KDD 1999 Data Set
KDD originally brought the idea of the data mining competition to the whole world. It has been of very good use for a long time thereby providing a very enriching experience. It poses a classification kind of problem having 4M rows and 48 columns in a 1.2GB file.
2. Chicago Crime Data Set
Data scientists nowadays are expected to handle very large volumes of data sets because companies no longer want to work on samples but use full data. Such data set will give you the necessary experience needed to handle such large datasets on any local machines you use. Although it is an easy problem, the main key actually management. It is a multi-classification problem with 6M observations.
3. Yelp Data Set
This data set is known to be a part of round 8 of the Yelp Dataset Challenge comprising of almost 200,000 images, within 3 JSON files of 2GB. The images in question offer information pertaining to local businesses in 10 cities across 4 countries. You will need to look for insights from data by using seasonal trends, cultural trends, social graph mining, text mining, infer categories, etc. so as to make it among the good data science projects.
4. Identify your Digits Data Set
You are allowed to study, analyze and recognize elements in images from this dataset. It is very similar to how the camera lens detects faces by making use of image recognition. You can build and test this technique; known to be a digit recognition problem. It has 7000 images with 28 X 28 size making it 31MB sizing.
5. Image-Net Data Set
This dataset offers various problems encompassing localization, object detection, screen praising and classification. With all its images freely available, you can look for any kind of image and create your project around it. For now, it has 14,197,122 images of various shapes with a size of 140GB.
Below are some of the examples of data sets and why you should take them:
1.) Titanic dataset from Kaggle:
This dataset is one major data set required for anyone who is just beginning data science. It has one good advantage – it appears to be simple at the beginning. However, it offers a very good understanding of the various things typical projects related to data science comprise of. Beginners can work on the data set using excel while pros can use advanced tools to work for extracting any hidden information and algorithms to substitute any missing values in the dataset.
2.) Learning to mine on Twitter:
This data science project for beginners project gives them the opportunity to understand the importance of data science. You can use Twitter and a good data science tool, you can get to know what is trending. Irrespective of whatever it is; whether it is politics, a recent movie, you get to know what is being said about by yourself. This exercise helps you understand the challenges faced in mining social media and also lets you know how easy it is integrating API in scripts for accessing any information on social media.