Every time you build new projects (Data Science projects in our case), you get to learn new technologies and their implementations with first-hand experience. In addition to mastering those technologies, your quest to learn more technologies related to Data Science ( in this case) increases and thus newer technologies come into the picture.
So, if you ask us whether building projects help in the learning process. Then it is a BIG YES from us! In addition to acquiring knowledge, you also gain immense confidence in the overall process and are trained to take up more responsibilities in your upcoming Data Science Project and so forth.
Learning stuff is great but building projects from the ground up covers it all!
That is the reason why, you might have observed, employers directly jump onto the project part in your resume. Above all, highlighting your top skills and abilities, the Data Science Projects in your resume speak for your hard work and your exposure & know-how. So, choosing projects that cover a lot of Data Science skills and at the same time are very useful to the organizations & public is the key to success.
So, we have come up with this intriguing list of Data Science projects that you pick from and get engaged in their making from scratch. Filled up to the brim with Data Science skills, these Data Science projects will keep you occupied and glued as they are equally interesting.
For your convenience, these Data Science projects are ordered in their respective difficulty levels. So that you can pick them accordingly and don’t puzzle them.
Basic Data Science Projects
1. Stack Overflow Survey Analysis
Paper surveys, mobile surveys, online surveys, be it any one of those, a well-planned survey will provide you with ample data! Above all, it helps to focus on your plan objectives and map your implementation.
This year in May, more than 80,000 developers on Stack Overflow shared their experiences stating- how they learn, the tools and languages they use, and provided all sorts of feedback valuable to Stack Overflow. These feedback reports are crucial for the improvement of the site and further development & progressive growth of both the parties involved.
If you are someone who turns back to Stack Overflow, like the millions of other programmers, then the Stack Overflow Survey Analysis project is going to be a must-build app for you!
For further details on the Stack Overflow Survey Analysis Data Science Project, refer to the table given below.
Project 1 Details:
| Data Science Project I | Stack Overflow Survey Analysis |
| Requirements | Preferred IDE for Python, Stack Overflow Survey Dataset (https://insights.stackoverflow.com/survey) |
| Project Flow | Firstly, import necessary libraries like Pandas, Numpy, matplotlib, etc. Read the Dataset. Analyze descriptive statistics using functions like describe(). Handle Missing Values. Data Cleaning using Pandas. Analyzing areas like Demographics, Distribution of Programming Skills, Experience, etc. And, Graphical Representation / Visualization. |
| Skills | Critical Thinking, Summarizing Data Characteristics, Spotting Anomalies. |
| Concepts | Exploratory Data Analysis, Summary Statistics, Graphical Representations. |
| Duration | 1-2 Days |
| Example present in the market | customer satisfaction survey, market research survey, employee satisfaction surveys |
So, get started with this data and prepare your first research survey analysis project. Here is a booklet that will help you prepare the questionnaire- Booklet for launching your survey project.
2. Market Basket Analysis
If you are a good Data Scientist already, the above image will speak a lot to you. However, for the newbies, let us tell you the above image gives a vague explanation of what rule is implemented in the Market Basket Analysis!
Market Basket Analysis is a data mining technique. And, it incorporates analyzing large sets of data concerning the customer product purchases that involve purchase history, products that are likely to be purchased together as in product groupings, etc. Most importantly, it helps the retailers to better understand the customer purchasing behavior and thereby increase sales accordingly.
The below table replicates the whereabouts of the Market Basket Analysis Project that you can take up as a beginner Data Scientist Project.
Project 2 Details:
| Data Science Project II | Market Basket Analysis |
| Requirements | Preferred IDE for Python, Theoretical Knowledge of Market Basket Analysis, Any Market Basket Analysis Dataset |
| Project Flow | Firstly, import necessary libraries like Pandas, Numpy, matplotlib, etc. Read the Dataset. Perform Data Preprocessing and Cleaning (If Necessary). Perform Apriori Analysis (Using apriori module) Define the minimum support and confidence for the association rule Take all the subsets in the transactions with higher support than the minimum support Take all the rules of these subsets with higher confidence than minimum confidence Sort the association rules in the decreasing order of lift. Then, visualize the rules along with confidence and support. |
| Skills | Unsupervised Learning Technique, Pattern Analysis, Background in statistics & Data Science, some algorithmic computer programming skills. |
| Concepts | Association Analysis, Apriori Algorithm |
| Duration | 4-5 Days |
| Example present in the market | Shopping Basket Analysis tool in Microsoft Excel |
While Market Analysis Projects are certainly useful from the retailer’s point of view. However, you can utilize this project for your personal business data analysis too. Then, build the project, add it to your resume and use the project for personal use or share the same with someone. In short, it’s a total win-win, you see!
3. Customer Churn Prediction
Moreover, based on the way customers use the products or services, customer retention can be predicted. Customer Churn Prediction is a very important project when it comes to business strategies.
FYI: Customer churn is the percentage of customers that stopped using your company’s product or service during a certain time frame.
One of the most important business problems is to predict customer churns, especially in the industries where the cost of customer accusation (CAC) is very high. By predicting customer churn well in advance, then acting towards avoiding the same (by bribing the customers with some gift vouchers or additional/ bonus benefits) can promote business growth to incredible levels.
If you know some business owners, who are making a big-time struggle to cope up with customer satisfaction and customer retention, then this project is the solution that you can deliver to them.
Then dive deep into the basic requirements of the Customer Churn Prediction project and laud this real-time project in your resume!
Project 3 Details:
| Data Science Project III | Customer Churn Prediction |
| Requirements | Preferred IDE for Python, Any Customer Churn Prediction Dataset |
| Project Flow | Firstly, import necessary libraries like Pandas, Numpy, matplotlib, etc. Data Collection and Preparation. Perform Data Preprocessing and Cleaning (If Necessary). Feature Engineering, Selection, and Extraction. Modeling using Logistic Regression, Decision Trees, and Other classification algorithms. Then, Testing and Validating Results |
| Skills | Supervised Learning Technique, Analyzing Historical Data, Forecasting, Features Manipulation |
| Concepts | Predictive Analytics, Regression, and Classification |
| Duration | 2-3 Days |
| Example present in the market | Telecom Churn Prediction |
So, these Data Science projects towards customer relationship management are very useful in the market. In short, building these Data Science projects will add stars to your resume.
Furthermore, moving on to slightly complex Data Science projects, coming up with intermediate-level Data Science projects.
Intermediate Data Science Projects
Above all, the projects we are trying to introduce are all real-time hits and are value-adds to the present market. So, you can make your project portfolio stand out from other Data Scientists by imbibing these Data Science projects. Then, work on the basic data here and derive the best out of it!
4. Chatbots– One of the best Data Science Projects
Next on our list of Data Science projects is the one that hardly needs an introduction! Chatbots that pop up almost from nowhere, are omnipresent these days.
Easy as it looks, this Data Science project involves a lot of skills to build one. So, have a look at the requirements of this Data Science project and quickly get started.
Project 4 Details:
| Data Science Project IV | Chatbots |
| Requirements | Firstly, preferred IDE for Python, Rasa, Conda Environment (For Rasa Dependencies) |
| Project Flow | Create a blank Rasa project using rasa init. Create intents, responses, and entities in the domain.yml file. Create chatbot conversation flow as stories in stories.yml file. Create custom actions for the bot using the actions.py file. Train the chatbot using the rasa train. Then, test the bot using rasa shell or RasaX for GUI-based interactions. |
| Skills | Rasa Framework, Intents, Entity, Actions, Stories |
| Concepts | Natural Language Understanding, Conversational AI Framework |
| Duration | 7-9 Days |
| Example present in the market | Meena: Google Chatbot, BlenderBot: Facebook AI Chatbot |
Build your customized chatbot with the help of the above information. Let your chatbot go wild and look exactly human-like! You can add more customizations to your chatbots, and who knows it will hit the market someday!
5. Recommendation Engine
Another intermediate Data Science Project on our list is the Recommendation Engine.
Recommendation Engines are also called the Recommender systems, or Recommendation Systems. Netflix, YouTube, Tinder, and Amazon, are all great examples of Recommendation Engines.
With information on past preferences, these recommendation systems analyze customer behavior and present the best recommendations. You can very well relate to this project already, right? Then quickly have a look at the project requirements and other details in the below table.
Project 5 Details:
| Data Science Project V | Recommendation Engine |
| Requirements | Preferred IDE for Python, Spotipy API Credentials |
| Project Flow | Firstly, create a token using Spotify API credentials. Extract metadata like song name, artist name, and URI.Extract Audio Features from URI. Perform Standardization and Principal Component Analysis. Follow any clustering approach for modeling. And, perform WCSS and Visualization (If Necessary) |
| Skills | Unsupervised Learning Technique, Clustering |
| Concepts | Dimensionality Reduction, PCA, Feature Scaling |
| Duration | 5-7 Days |
| Example present in the market | Netflix, YouTube, Amazon, etc |
This perfect marketer tool especially for e-commerce / online businesses is very useful and can increase turn around (sales, profits, etc.)of your business dramatically. So, build this intriguing Data Science project and implement it for your benefit. 😉
Advance Data Science Projects
Progressing ahead with more advanced Data Science Projects. Likewise, adding to the list of Data Science projects, the coming-up projects incorporate in-depth and more underlying concepts of Data Science.
6. Stock Price Prediction
Further, in the era of big data, deep learning will easily assist you to predict the future value of any company stock. Above all, Stock Price Prediction Project is an essential tool for predicting stock market prices. To sum up, this project is trending now and can add augmented value to your project portfolio.
If you are interested to know more about this intriguing Data Science project, then scroll down and look into the table.
Project 6 Details:
| Data Science Project VI | Stock Price Prediction |
| Requirements | Preferred IDE for Python, Any Stock Price Dataset (OHLC format) |
| Project Flow | Firstly, import necessary libraries like Pandas, Numpy, matplotlib, etc. Read the Dataset. Perform Data Preprocessing and Cleaning. Encode the Dates. Perform Feature Engineering using Dates. Try to collect directly and inversely related data to include in the model. Model using Long Short Term Memory or any other ARIMA approach. Finally, Train, Test, and Validate the results. |
| Skills | Neural Networks, Predictive Analysis, ARIMA |
| Concepts | Deep Learning, LSTM, Stock Price Analysis |
| Duration | 7-9 Days |
| Example present in the market | Google Stock Price Prediction Using LSTM |
This real-time project is certainly worth building. So, make your best efforts to build it with all your Data Science flair.
7. Image Captioning
The last Data Science Project on our list here is the Image Captioning project.
When we see an apple, our brain processes the information and tells us that the red ball-like object is an apple and that we can eat it!
But can a computer understand and process the image information similarly?
In short, YES is the answer as on date. While not really thought of some years back, this Data Science project is an outcome of the very recently brought to light concepts of computer vision and natural language processing (NLP).
Above all, an image captioning project can recognize the context of an image and describe it in a natural language like English.
Now if you are already jumping with joy to get started, then the below table is where you need to move to.
Project 7 Details:
| Data Science Project VII | Image Captioning |
| Requirements | Preferred IDE for Python |
| Project Flow | Firstly, import necessary libraries like Tensorflow, matplotlib, NumPy, PIL, etc. Read the Dataset (Example: MS-COCO). Process the Image using InceptionV3. Cache the extracted features. Preprocess and Tokenize the captions. Finally, Train and Test the model. |
| Skills | Image Processing, Tensorflow, Keras, Neural Networks |
| Concepts | Deep Learning, Handling Large Datasets |
| Duration | 9-12 Days |
| Example present in the market | Social Media platforms like Facebook (can infer directly from the image, where you are beach, cafe, etc.). |
Wow, we are sure this project will keep you awake till you finish it because it is so interesting and so real!
Wrapping Up
In short, these Data Science projects are must-build projects for any budding Data Scientist. So, if you aspire to build a lucrative career in Data Science, make sure to add these projects to your project portfolio and make it stand out!
Master Data Science from IIT-M Experts
Similarly, we have saved more amazing Data Science Projects for you. So, why don’t you share your contact and let us get back to you? After that, let us discuss how to take your Data Science career to great heights?
