Top data science projects to get hired in 2022

  

Data Science is a way for assisting in the solution of real-world problems by leveraging appropriate data information as inputs. You've put in your time and developed data science abilities, but you're still looking for work in the field. The application of relevant data to real-world problems is known as data science. If you're in the same boat, now is the time to start working on some data science projects and enroll for data science course. By making good use of relevant data, Data Science aids in the solution of real-world problems.

They aid in the detection of frauds, the forecasting of market sales, climate change, and even the possibility of a person developing heart disease. In today's world, businesses are relying on data science professionals to understand customer behavior, forecast sales, and forecast the product's future in the market. The rising use of artificial intelligence in today's society has resulted in a higher demand for data science, and role of data scientist have become more important. Companies are now utilizing this information to better understand customer behavior, forecast sales, automate internal procedures, and estimate the future of a product in the market where it is being introduced.

This is why employers looking for data science specialists prefer a Data Science Course from a reputable university with a curriculum tailored to develop industry-valued abilities. Data scientists are in high demand all across the world as a result of this. As a result, I'm going to present some of the Best Data Science Projects for Getting Hired. This is why companies hire data scientists who have finished Data Science Programs at respected universities and have a curriculum that emphasizes the development of industry-valued skills. Like at Learnbay, we give the best data science course in Bangalore and help you to make your dream come true. These projects will undoubtedly enhance your resume and set you apart from the rest of the data science crowd.

It is critical to include some sharp and new data science initiatives on your resume in order for it to stand out from the crowd. You must add some intriguing data science activities to your CV in order for it to stand out. Today's tech-savvy students who want to pursue employment in this industry prefer the Data Science course.

Top data science projects in 2022

We've compiled a list of data science projects that can help you develop a good profile in this blog. Now, without further ado, let's go to work on discovering the top data science projects to land a job-

●   Sentiment Analysis

●   Parkinson’s Disease Diagnosis

●   Customer Segmentation

●   Fake News Detection

●   Movie Recommendations

●   Classifying Breast Cancer

●   Credit Card Fraud Detection

●   Recognizing the speech emotions

Sentiment analysis

Sentiment analysis is a method of analysing targeted customers' thoughts about a company's product or service. As a result, sentiment analysis is a tool for analysing people's opinions about a certain product, service, or choice. Businesses utilise it to determine how well their products or services are received. The polarity of the opinions might range from favourable to negative.

The response range can be kept binary, such as Positive or Negative. It explains why sales targets aren't being fulfilled or why a product or service isn't selling well. As a result, the data science project can make use of the R programming language, which can assist in drawing important inputs and then analysing them to obtain the essential information from the study effort. To extract insights from the data for this project, NLP, text analysis, computational linguistics, and biometrics are used. In the sentiment analysis, general-purpose lexicons such as bing, Loughran, and AFINN can be used.

●      Source code: Sentiment Analysis Project in R

●      Libraries (guides included): Pandas, Scikit-learn

●      Language: R

●      Package: JaneaustenR

Parkinson's disease diagnosis

Data analytics could be used to diagnose Parkinson's disease early on and acquire control over the disease's symptoms and signals. With XGBoost, you can identify Parkinson's illness using Python as the coding language. The patient will benefit from a better health service as a result of this. XGBoost is a free software library that supports a variety of languages and libraries, including C++, R, Python, Java, Julia, and others. Data Science could be used to make early predictions for Parkinson's disease and obtain various benefits in terms of prognosis.

Early Parkinson's disease predictions can be generated using this data science course. TIn this data science research, the Python language could be used to assess the conditions of people who are prone to, vulnerable to, or show indicators of being impacted by Parkinson's disease. Patients who are at risk of developing Parkinson's disease or who are showing signs of the condition in the future can be notified, and better health care can be provided to them.

A data science certification course is offered by Learnbay: one of the best data science course in Bangalore, that will help you become a data-driven decision-maker with live virtual teaching, hands-on projects, and mentorship from industry practitioners.

●      Code: Detecting Parkinson’s Disease with XGBoost

●      Language: Python

●      Package: UCI ML Parkinson's dataset

●      1.5 Color Detection with Python

Customer segmentation

Businesses are constantly seeking ways to segment their clients so that customer-specific tactics and product placement can be developed to meet their needs. The segmentation process ensures that the company can develop a consumer-specific strategy and a product or service that meets its requirements. If you have a Data Science Project on Customer Segmentation, you will undoubtedly have a competitive advantage over other candidates.

Before launching any online marketing campaign, this is a must-do action. Customer segmentation is also known as unsupervised learning, in which a corporation uses clusters to classify and categorise its customers into different groups based on age, area, gender, interest, habits, preferences, and other factors. This project can also be used to identify client inputs such as annual incomes and spending patterns in order to develop a strategy for that segment. You can use their annual incomes, preferences, and spending scores from a specific time period as inputs.

●      Source code: Customer segmentation with machine learning

●      Language: R

●      Package: Mall_Customers Dataset

Fake News Detection

It's difficult to tell when something is fake. You can make a Python project out of this data science project concept. Fake news is widely disseminated around the globe. So, how can we tell the difference between true and false news? Python is used to provide the solution. JupyterLab is a web-based user interface that lets you work

with documents and activities like Jupyter notebooks, text editors, terminals, and custom components in an integrated and expandable way.

News is disseminated through various mediums, but determining its accuracy is challenging, and the rise of fake news has serious ramifications. In this assignment, you must use the Python programming language to create a model that can determine whether the news is true or false. In this situation, a data set with dimensions of 7796*4 will be extremely useful.

To complete this project, use a TfidfVectorizer and utilise a PassiveAggressiveClassifier to divide news into "Real" and "Fake" categories. To learn more about this project, sign up at one of the best data science course in Bangalore and go on with it.

•           Language: Python
•            Dataset/Packages: news.csv
•  Libraries (guides included): Scikit learn (TfidfVectorizer and PassiveAggressiveClassifier),  Pandas and Numpy

Movie recommendations

This concept will captivate a large number of individuals. A movie recommender assists a user in discovering further content that they may love. You can use the R programming language to create a Data Science project that recommends movies based on a machine learning approach. It creates a personalised list for each user depending on their preferences. We all appreciate being given movie or television show recommendations to binge-watch. Using a screening procedure based on the preferences of other users who have already watched the movie, his machine learning will make recommendations to users.

The inputs of first-time viewers will be gathered for this project, and their comments will be categorised. These suggestions could be based on your browsing history, what other individuals with similar demographics/traits are watching, and so on. Additionally, browsing history data can be used to illustrate the level of interest and craze that has surrounded the film. The R programming language can be used to create this movie-recommender system. For this research, MovieLens will be an amazing dataset.

●      Source Code: Movie Recommendation System Project in R

●      Language: R

●      Package: MovieLens dataset

 

Classifying Breast Cancer

Breast Cancer Classification is yet another medical advancement made possible by data science certification course and AI. You can develop a Data Science Project using the IDC regular dataset to help detect the presence of IDC, or Invasive Ductal Carcinoma, in the female chest, which is the most frequent type of breast cancer. It begins in a milk duct and spreads outside the duct, attacking fibrous or fatty breast tissue. For categorization in this data science project concept, you'll need to use Deep Learning and the Keras library. The Deep Learning and Keras libraries can be used to classify breast cancer.

●      Source Code: Breast Cancer Classification with Deep Learning

●      Language: Python

●      Package: IDC_regular

Credit Card Fraud Detection

As a result, developing a data science project to detect credit card fraud could be really beneficial. In this project, you will use R programming and algorithms such as Decision Trees, Logistic Regression, Artificial Neural Networks, and Gradient Boosting classifiers to detect credit cards. You can utilise the R programming language in this project, as well as algorithms like Decision Trees, ANNs (Artificial Neural Networks), and Logistic Regression. You'll use the Card Transactions dataset to distinguish between fraudulent and legitimate credit card transactions.

The utilisation of a Card transaction dataset is also required to differentiate between authentic and fraudulent credit card transactions. You'll also use various machine learning techniques and plot performance curves to assess accuracy. This Data Science Project also allows for the installation of alternative models and the visualisation of performance curves which clearly would explained in data science certification course.

●      Source: Credit Card Fraud Detection using Machine Learning

●      Language: R

●      Package: Credit Card transactions dataset

Recognizing the speech emotions

This method makes an attempt to distinguish the voice tone and pitch change that occurs when a person speaks after listening to a specific subject. You must create a model that can distinguish human emotion and affective states from a speech in this project. The RAVDESS dataset is used in conjunction with the mfcc, chroma, and mel features to recognise the emotion associated with a specific voice tone. One of

the most difficult jobs in the speech signal analysis arena is speech emotion recognition (SER). This allows us to create an MLPClassifier for this type of model. Speech Emotion Recognition has applications in a variety of industries, including customer service, recommender systems, and the medical industry.

●      Code: Speech Emotion Recognition with Librosa

●      Language: Python

●      Package: RAVDESS dataset

Final Lines

It is entirely up to you to choose the Data Science Project of your choosing, but it is critical that you complete one and make it a highlight on your resume. No data science project is tough if you have a sufficient understanding of the appropriate tools and procedures. This appeal will undoubtedly persuade the hiring manager that you possess all of the necessary talents and are even knowledgeable about the type of service they seek. In reality, working on a variety of projects is the best way to test a technology's actual use.

So sit back, relax, and choose one of the top 8 Data Science Project ideas listed above to work on and include in your resume, and prepare to amaze them so much that they will want you to join them right away. It provides you with the appropriate amount of exposure while also improving your problem-solving abilities.

This was our choice of the 8 most promising data science projects for 2022. You can enrol in Learnbay Graduate Program in Data Science course in Bangalore, which includes 12+ industry projects, real-life projects, and Program Manager support throughout the programme.

 

All the Best for your Data Science Journey!

      Happy Learning!