App Reviews Sentiment Analysis means evaluating and understanding the sentiments expressed in user reviews of mobile applications (apps). It involves using data analysis techniques to determine whether the sentiments in these reviews are positive, negative, or neutral. If you want…
Marketing is a fundamental business activity aimed to promote and sell products or services to customers. The primary goal of marketing is to understand customer needs and preferences, create products or services that meet those needs, and effectively communicate their…
Merging of Datasets in Data Science is the process of combining multiple datasets into a single, unified dataset. It is done to create a more comprehensive and complete dataset for analysis. If you want to learn the techniques used for…
Cohort Analysis is a data analysis technique used to gain insights into the behaviour and characteristics of specific groups of users or customers over time. If you want to learn how to perform Cohort Analysis, this article is for you.…
Tableau is a powerful data visualization tool used by Data Science professionals to transform raw data into interactive and understandable visualizations. It allows users to connect to various data sources, create dynamic charts, graphs, maps, and dashboards, and share these…
Machine learning is an advanced technology that now has been used for developments of so many fields and industries. Aside from website and app building, some businesses have successfully implemented this technology to improve the quality of their products and…
Hypothesis testing is a statistical method used to make decisions about population parameters based on sample data. It involves formulating null and alternative hypotheses, collecting data, and using statistical tests to determine the validity of the null hypothesis. If you…
Data science broadly encompasses data analysis, machine learning, data engineering, and statistical modelling. The path you take can vary based on the role you’re aiming for, such as a Data Analyst, Data Scientist, Machine Learning Engineer, or Data Engineer. So,…
Hypothesis testing is a statistical method used to make decisions about population parameters based on sample data. It involves formulating null and alternative hypotheses, collecting data, and using statistical tests to determine the validity of the null hypothesis. Hypothesis testing…
Hypothesis Testing is one of the most valuable concepts for Data Science professionals. Significance level (alpha) and p-values are fundamental concepts in hypothesis testing. The significance level determines the risk of Type I errors, while p-values quantify the strength of…
Data Transformation involves converting and modifying data from its original format into a more suitable format for analysis. It aims to enhance the quality, usability, and effectiveness of the data for various analytical tasks. If you want to learn how…
E-commerce, short for electronic commerce, refers to the buying and selling of goods and services over the Internet. In E-commerce, businesses set up online platforms (websites or mobile apps) to showcase their products or services. Customers browse through these platforms,…
SQL is one of the most valuable tools for data professionals. Data professionals use SQL queries to extract relevant data for analysis. If you want to build an SQL project for Data Science but don’t know how to get started,…
Data Manipulation means altering, transforming, or restructuring data to prepare it for analysis, reporting, or other data-related tasks. It is a fundamental step in data management and analysis, as raw data often needs to be cleaned, organized, and refined to…
Customer Behavior Analysis is a process that involves examining and understanding how customers interact with a business, product, or service. This analysis helps organizations make informed decisions, tailor their strategies, and enhance customer experiences. If you want to learn how…
In a Data Science interview, candidates are often assessed on their knowledge of statistics, as statistics is a fundamental component of data analysis and modelling. If you want to know what kind of interview questions based on statistics you can…
Data Visualization is the graphical representation of data to help individuals, including Data Scientists and decision-makers, comprehend, analyze, and draw insights from complex datasets. It involves using various visual elements such as charts, graphs, plots, and maps to present data…
In the Finance domain, there are various Data Science jobs for leveraging data-driven insights to make informed financial decisions, manage risks, detect fraud, and optimize investment strategies. If you are interested in the Finance domain and want to know the…
A Book Recommendation System is a data-driven application designed to suggest books to users based on their preferences, reading history, and behaviour. It employs various data science and machine learning techniques to provide personalized book recommendations, enhancing the reading experience…
The retail domain refers to the sector of the economy that involves the sale of goods and services to consumers for their personal or household use. Retailers purchase products from manufacturers or wholesalers and then sell them to individual consumers…
Scikit-learn is a powerful library that provides a wide range of tools for data preprocessing and machine learning. It is built on top of other popular Python libraries like NumPy, SciPy, and Matplotlib, making it an integral part of the…
Ads CTR Analysis stands for Click-Through Rate Analysis for advertisements. Ads CTR Analysis is the process of examining the effectiveness of online advertisements by measuring the rate at which users click on an ad’s link to reach the advertiser’s website.…
Data analysis is the systematic process of inspecting, cleaning, transforming, and interpreting raw data to uncover meaningful patterns, trends, and insights. If you are looking for a job as a Data Analyst, you need to have some Data Analysis projects…
Time Series Forecasting is a statistical technique used to make predictions based on historical time-ordered data points. It’s valuable when dealing with data that changes over time, such as stock prices, sales figures, weather data, or economic indicators. ARIMA and…
There are various Data Science roles in the industry. Each role requires you to be an expert in some specific skills to get your first Data Science job. If you want to know what skills you should have for your…
Market Basket Analysis is a data-driven technique used to uncover patterns and relationships within large transactional datasets, particularly in retail and e-commerce. It helps businesses understand which products or items are often purchased together, providing insights for optimizing product placement,…
SQL is a language that allows users to communicate with relational databases, which are structured storage systems designed to organize and store data in tables. These tables consist of rows and columns, much like a spreadsheet. SQL provides a standardized…
Stock Market Comparison Analysis is the process of evaluating and comparing the performance of multiple stocks or financial instruments within the stock market. It aims to provide insights into how different stocks have performed relative to each other and the…
Neural network architectures refer to the structural and organizational designs of artificial neural networks (ANNs). These architectures determine how the network is organized, including the number of layers, the number of neurons in each layer, the connections between neurons, and…
Data Resampling is a technique used in Data Science to adjust the size or distribution of a dataset. It involves modifying the existing dataset by either increasing or decreasing the number of data points. If you want to learn how…
Data Science means using data and computer science to solve business problems. There are various problems in Data Science that a Data professional deals with daily. If you want to know about the types of problems we deal with in…
Machine Learning means using data and algorithms to build intelligent systems. There are various Machine Learning algorithms used for training models that help in solving problems and building intelligent systems. While learning Machine Learning, many people are often confused about…
In Machine Learning, Feature Selection is the process of choosing a subset of relevant and significant features (variables or attributes) from features available in a dataset. The goal of selecting features is to improve the performance of a Machine Learning…
Data Visualization is a critical aspect of data science and analytics. It refers to presenting data in graphical or visual formats, such as charts, graphs, and maps, to help people understand the patterns, trends, and insights hidden within large and…
Customer Acquisition Cost (CAC) Analysis is a critical aspect of business strategy where Data Science plays a vital role. CAC refers to the cost a company incurs to acquire a new customer. Understanding and optimizing this cost is crucial for…
“Machine Learning Algorithms: Handbook” is a book based on a step by step guide to all Machine Learning algorithms with implementation using Python. In this article, I’ll give you a complete overview of the book so that you can understand…
Many people find solving a Data Science problem difficult even after mastering Machine Learning algorithms. The problem is that they focus more on algorithms than skills and the mindset of working with data. Data Science is not all about mastering…
Data manipulation is a fundamental process in data science that involves making changes, transformations, or adjustments to raw data to prepare it for analysis. This process is critical because real-world data is often messy, incomplete, or in a format that…
Cloud platforms, also known as cloud computing platforms, are comprehensive services provided by technology companies like Amazon, Microsoft, Google, and IBM, among others. These platforms offer a wide range of computing resources, including servers, storage, databases, networking, analytics, Machine Learning,…
Air quality index (AQI) analysis is a crucial aspect of environmental data science that involves monitoring and analyzing air quality in a specific location. It aims to provide a numerical value representative of overall air quality, essential for public health…
Domain knowledge refers to expertise and understanding of a specific field or subject matter. It encompasses the concepts, terminology, practices, and challenges associated with that domain. In Data Science, domain knowledge means a deep understanding of the industry, business, or…
Feature Engineering is a critical step in solving a Data Science problem that involves creating or selecting the most relevant and informative features (input variables) from raw data. These features are then used to train machine learning models, so the…
Data storytelling is a compelling way of communicating insights and information derived from data by constructing a narrative around it. It involves presenting data-driven findings in a clear, engaging, and relatable manner, similar to how a storyteller weaves a tale.…
Dating Recommendation refers to using data-driven techniques to provide personalized matchmaking suggestions to individuals seeking partners through online dating platforms. These recommendations are based on various factors and preferences, aiming to increase the likelihood of successful and compatible matches. If…
In Data Science interviews, technical questions are designed to assess your fundamentals of working with data and your understanding of using Data Science concepts in a given problem. If you want to understand what types of questions are asked in…
Everyone has their own way of approaching a Data Science problem. If you are a beginner in Data Science, then your way of approaching the problem will develop over time. But there are some steps you should follow to start…
Fitness Watch Data Analysis involves analyzing the data collected by fitness wearables or smartwatches to gain insights into users’ health and activity patterns. These devices track metrics like steps taken, energy burned, walking speed, and more. So, if you want…
Supply Chain involves coordination among various entities, such as suppliers, manufacturers, distributors, retailers, and customers, to optimize the process to minimize costs, enhance quality, and meet customer demands. If you are aiming for a Data Science job in retail, manufacturing, logistics,…
Demand Forecasting means estimating future customer demand for a product or service based on historical data and relevant factors. Inventory Optimization is the strategic management of inventory levels to ensure that the right amount of goods is available at the…
While learning Data Science, the decision between pursuing a degree or opting for courses and certifications can significantly impact your career trajectory. Your educational background plays a crucial role in determining the most suitable path for your journey in data…
In the Finance industry, various institutions and entities come together to facilitate financial transactions, manage risks, allocate resources, and make informed decisions, including commercial banks, investment banks, asset management firms, insurance companies, stock exchanges, regulatory bodies, and more. If you…
Python is a popular programming language for Data Analysis for several reasons. In the same way, Tableau and Power BI are powerful tools used in the industry for Data Analysis. It confuses a lot of people, especially beginners, why we…
Marketing is a strategic and dynamic process to promote products or services to a target audience. It involves activities that create awareness, generate interest, and influence consumer behaviour. If you are aiming to work as a Data Science professional in…
Hyperparameter tuning is an essential process in Machine Learning that involves optimizing the settings that guide the training of a Machine Learning model. But these settings themselves are not learned from the data. These settings, called hyperparameters, play a vital…
In Data Science, time series refers to a sequence of data points recorded at specific time intervals. Time series data captures observations over time, where each data point corresponds to a particular moment or period. Time series analysis involves uncovering…
Data cleaning, also known as data cleansing or scrubbing, is a crucial step in data preparation and analysis. It refers to the systematic and meticulous identification, correction, and removal of errors, inconsistencies, and inaccuracies from data. The main objective of…
Forecasting the number of subscriptions Netflix will achieve in a time period is a vital business practice that enables them to plan, strategize, and make data-driven decisions. It enhances operational efficiency, financial planning, and content strategy, ultimately contributing to their…
In today’s competitive Data Science field, employers prefer candidates who can seamlessly bridge the gap between working with data and domain knowledge. By delving into projects that align with specific industries, you can demonstrate a deep understanding of the domain’s…
Plotly is a powerful and versatile data visualization library used by Data Science professionals to create interactive and visually appealing plots, charts, and graphs. It enables users to represent complex datasets in a graphical form, making it easier to comprehend…
If you are looking for your first data science job, you need advanced and unique projects mentioned in your resume. A data science professional works with APIs to collect real-time data from company databases and third-party applications. Having at least…
A Music Recommendation System is an application of Data Science that aims to assist users in discovering new and relevant musical content based on their preferences and listening behaviour. Personalized music recommendations have become an essential tool in the digital…
Data analysis is the systematic process of inspecting, cleaning, transforming, and interpreting raw data to uncover meaningful patterns, trends, and insights. A data analyst is a Data Science professional skilled in working with data and equipped with the necessary tools…
Outliers are data points that deviate significantly from the rest of the data. These data points lie far away from the majority of the data points and can have a substantial impact on statistical analysis and modelling. If you want…
Recommendation systems are one of the popular applications of Data Science in every domain. The recommendation system of Amazon works by using both collaborative filtering and content-based filtering techniques. Amazon uses collaborative filtering to analyze user behaviour and recommend products…
Many web platforms and applications perform A/B testing to run experiments to find the best design, layout, or themes for their platform. Instead of relying on assumptions or hunches, applications and websites can test different design variations on real-time users…
Data Analysis means understanding the story behind the numbers. It is a systematic process of examining, cleaning, transforming, and interpreting raw data to uncover the story behind the data points. If you are learning Data Analysis, one of the best…
SQL is widely used in Data Science because it allows data science professionals to extract and manipulate data efficiently from databases. It is a powerful language for managing and analyzing structured data. If you are looking for some practical SQL…
Matplotlib is a popular data visualization library for Python. It provides functions and tools enabling data scientists to create various plots and charts. Matplotlib allows data scientists to create high-quality visualizations that effectively communicate insights and patterns hidden within the…
Python and R are preferred languages for data science due to their rich ecosystem of libraries, extensive community support, and powerful tools for statistical analysis, data manipulation, machine learning, and visualization. You can choose either Python or R for Data…
Pandas is a powerful open-source library in Python that provides high-performance data manipulation and analysis tools. Pandas enhances the productivity and efficiency of Data Science professionals by providing a comprehensive set of tools for data manipulation, analysis, and exploration. Its…
User Engagement Analysis is a data-driven approach to assess and understand user involvement, interaction, and satisfaction with a product, service, or platform. It involves analyzing various metrics and behavioural patterns to gain insights into user behaviour and preferences. It aids…
NumPy, which stands for Numerical Python, is a powerful library in Python providing support for large, multi-dimensional arrays and matrices, along with a vast collection of mathematical functions to operate on these arrays. It serves as a fundamental building block…
There are various Data Science tools used in the industry. The usage of different data science tools across companies and professions stems from the diverse nature of their data, objectives, and roles within the industry. Companies, ranging from small startups to large…
Market basket analysis is a Data Science concept that aims to understand customers’ buying habits to uncover associations and relationships between products. It focuses on analyzing the contents of customers’ shopping carts to identify frequently purchased items together. If you…
Dynamic Pricing is an application of data science that involves adjusting the prices of a product or service based on various factors in real time. It is used by companies to optimize revenue by setting flexible prices that respond to…
Mentioning projects in a resume is of the utmost importance as it allows potential employers to assess your practical skills and abilities. For Data Science jobs, it is essential to mention projects in your resume the right way, as it…
RFM analysis stands for recency, frequency, and monetary value analysis. It is a data science concept used in marketing and customer relationship management. It involves analyzing customer behaviour and segmenting customers based on their transactional history, specifically focusing on three…
Data preprocessing is a critical step in data science tasks, ensuring that raw data is transformed into a clean, organized, and structured format suitable for analysis. A data preprocessing pipeline streamlines this complex process by automating a series of steps, enabling data…
Nike is an American multinational corporation engaged in the design, development, manufacture, marketing and worldwide sale of footwear, apparel, sports equipment, accessories and services. There are many ways how Nike uses Data Science to stay ahead of its competitors worldwide.…
ARIMA (autoregressive integrated moving average) is a widely used statistical model for time series analysis and forecasting. It combines three key components: autoregression (AR), differentiation (I), and moving average (MA). In ARIMA models, the p, d, and q values are…
RFM Analysis is used to understand and segment customers based on their buying behaviour. RFM stands for recency, frequency, and monetary value, which are three key metrics that provide information about customer engagement, loyalty, and value to a business. So,…
Customer Segmentation is used to divide a company’s customer base into distinct groups based on common characteristics. It helps companies better understand their customers. If you want to understand Customer Segmentation and how Data Science professionals use this technique, this…
Exploratory data analysis (EDA) is a Data Science concept where we analyze a dataset to discover patterns, trends, and relationships within the data. If you want to understand Exploratory Data Analysis, this article is for you. In this article, I will…
The problem of deleting duplicate emails is a popular SQL question in Data Science interviews. It involves identifying and removing duplicate records from a table that stores email addresses. So, if you want to know how to solve this problem,…
Exploratory data analysis (EDA) is a Data Science concept where we analyze a dataset to discover patterns, trends, and relationships within the data. It helps us better understand the information contained in the dataset and guides us in making informed…
The currency conversion rate or exchange rate is an important economic indicator affecting several sectors, such as import-export businesses, foreign investment and tourism. By analyzing past data and predicting future exchange rates, we can gain valuable insights to help stakeholders…
Lifetime value analysis calculates the expected value a customer/user will generate over the lifetime of their relationship with the company. So, if you want to know what Lifetime Value Analysis is and how a Data Science professional can help businesses…
The problem of employees earning more than their managers is a popular SQL question asked in Data Science interviews. It involves querying a database to identify employees earning a higher salary than their respective managers. So, if you want to…
H&M is a Sweden-based multinational clothing company that focuses on fast fashion clothing for men, women, teens and children. It is one of GenZ’s favourite brands worldwide. There are many ways in which H&M uses data science to keep its…
In today’s fast-paced e-commerce industry, fast and efficient order delivery is crucial to business success. To ensure seamless order fulfilment, businesses often partner with courier companies to ship their products to customers. However, managing the charges collected by these courier…
Demographic Analysis refers to analyzing data about a population, such as age, gender, income, education, and location, to better understand its characteristics, behaviour, and preferences. So, if you want to know what Demographic Analysis is and how a Data Science…
The problem of Customers Who Never Order is a common SQL question asked in Data Science interviews. It means querying a database to identify customers who have never placed an order. So, if you want to know how to solve…
A Business Analyst is a Data Science professional who uses the data generated by the business to analyze and forecast the performance of a business, design and manage the creation of new data products, and bridge the gap between business stakeholders and…
Analyzing and Forecasting Time Series is a statistical technique used to analyze data points collected over time. It helps companies identify patterns and trends in the data, which can be used to make informed decisions about the future. So, if…
Stock Market Performance Analysis involves calculating moving averages, measuring volatility, conducting correlation analysis and analyzing various aspects of the stock market to gain a deeper understanding of the factors that affect stock prices and the relationships between the stock prices…
Cohort Analysis is one of the real-time concepts that every Data Science professional should know. Cohort Analysis helps companies analyze and understand the behaviour of their customers or users over time. So, if you want to know what Cohort Analysis…
Customer lifetime value analysis is used to estimate the total value of customers to the business over the lifetime of their relationship. It helps businesses make data-driven decisions on how to allocate their resources and improve their customer relationships. So,…
A/B Testing is one of the real-world concepts you need to know as a Data Science professional. A/B Tests help businesses compare two different options or strategies, such as two different advertisements or website designs, to see which performs better…
Not everyone is always available on social media all the time. Some people limit the use of social media during festive seasons, while some avoid social media during their examinations. So, as Content creators, we need to decide when to…
Content-based filtering and collaborative filtering are two common approaches used in recommendation systems. A Content-based recommendation system uses information about the recommended item, while a collaborative system uses user behaviour data. So, if you want to know how these approaches…
As Data Science beginners, sometimes we need to find datasets to work on projects. And as Data Science professionals, we sometimes need to find synthetic data based on the problem we are working on. So, if you want to know…
Store sales and profit analysis is the task of analyzing the performance of a retail store in terms of its sales and profits. It helps businesses identify areas for improvement and make data-driven decisions to optimize their operations, pricing, marketing,…
Data-driven business models are the types of business models in which data is used for overall business operations. Most big tech product companies you hear about today have data-driven business models. So, if you want to understand what Data-Driven business models…
User Funnel Analysis is a way to analyze the flow of users on a website or an application. It helps analyze the conversion rate on each page visited by the users. So, if you want to know how to analyze…
The supply Chain is the network of production and logistics involved in producing and delivering goods to customers. And Supply Chain Analysis means analyzing various components of a Supply Chain to understand how to improve the effectiveness of the Supply…
The first step to getting a job today is to create and upload your resume. The way you used to create a resume some years ago is very different from the way companies want you to. So, if you want…
Myntra is one of the fashion e-commerce platforms in India. It is known for its trending collection of clothing, footwear, and accessories. Myntra uses a lot of Data Science techniques that make it different from other e-commerce platforms. So, if…
You must have observed that some applications on your smartphone don’t charge anything but are still profitable. Most companies that are free for a user make money with the data of the users. So, if you want to know how…
The price of a product is one of the most important decisions for every business. It means setting a price for a product or service that is affordable to the target consumer and helps the business remain profitable in the…
Data Preparation is one of the most valuable skills every Data Science professional should have. One challenging task in data preparation is filling in missing values and deciding what measure you should consider between mean, median, and mode to fill…
Accelerometer is a device used to measure the acceleration or vibrations of a motion. The data provided by an accelerometer is three-dimensional and can be used in data-driven applications for solving problems like fall detection and health monitoring. So, if…
Supply Chain Management is the management of the flow of goods from raw materials to the final products and ensuring the delivery of the demanded products at the right place and at the right time. There are many use cases…
There are many types of questions you are asked for a job interview to understand your behaviour, technical skills, domain expertise, and how you will use your skills in solving real-time business problems. If you are looking for some of…
Employee attrition analysis means analyzing the behaviour of the employees who left your organization and comparing them with the current employees in your organization. It helps in finding which employee may leave soon. So, if you want to learn how…
LinkedIn is a social media platform for working professionals. People use LinkedIn to know about industry trends, job seeking, and growing their professional network. So, if you want to know how LinkedIn uses Data Science, this article is for you.…
Customer Retention means keeping the existing customers loyal towards the business. Retaining customers helps businesses in repeat orders, profitability, and goodwill which attracts more new customers. Today businesses use your data to formulate strategies to retain you as a customer.…
Demand and Supply Analysis is a valuable concept used to analyze the relationship between the quantity demanded and the quantity supplied. If you want to learn about demand and supply analysis and how it helps businesses in the real world,…
Twitter is one of the popular social media applications today. It is known for expressing views in a short piece of text which makes it different from other social media applications. So, if you want to understand how Twitter uses…
Advertising is a marketing strategy that businesses use to promote their products and services. Advertising is not a new concept, it has been used by businesses of all sizes to get more customers over the years. So, if you want…
A recession is an economic situation that arrives when the circulation of money in the economy is low for two consecutive quarters. When the circulation of money is low, it means people are not spending money in the market. When…
Mastercard Inc. is the second largest payment processing corporation worldwide. It offers a range of payment and financial services to businesses and customers worldwide. So, if you want to know how Mastercard uses Data Science for its business, this article…
There is a huge competition in the Data Science field, making it hard to mention unique projects on your resume. An interviewer goes through hundreds of projects every day, so it’s essential to mention unique projects on your resume so…
Samsung is a South Korean multinomial conglomerate. It is known for its midrange and flagship smartphone collection worldwide. There are many ways how Samsung uses Data Science and Machine Learning techniques in its technology and business. So, if you want…
Your LinkedIn profile is like an online resume. Today, companies do have a look at your LinkedIn profile before hiring you, especially in the tech industry. So, if you want to know how to create a LinkedIn profile to get…
There have been many innovations in the healthcare industry since the outbreak of covid in 2019. The use of data in the healthcare industry has helped healthcare professionals get more accurate information about the medical conditions of patients. In this…
Data Analysis means analyzing data to gather valuable insights that can be used in decision-making and solving various business problems. The role of a Data Analyst is one of the best jobs to start your journey as a Data Science…
Algorithmic Trading is the use of algorithms in the financial market to make trading decisions. JP Morgan Chase & Co. is one of the businesses that use Algorithmic Trading for investment decisions. So, if you want to learn how to…
Tata Consultancy Services is an Indian multinational corporation that provides IT, data processing and consulting services. TCS is one of the highly active recruiters in India for its IT and data processing services. So, if you want to know how…
Dream11 is a fantasy sports platform where you can create a virtual team of real sports players and participate in fantasy games. Dream11 has many use cases of Data Science that make it different from all other fantasy gaming applications.…
A box plot is a data visualization technique for analyzing the distribution and patterns of numerical data points. Understanding data visualization graphs is not easy for everyone. So if you want to know how to analyze a box plot, this…
A career aspirations survey gathers information about the goals and aspirations of people in their careers. It includes questions based on long-term goals, preferred work environment, interests, and values. So, if you want to learn how to analyze the information…
JP Morgan Chase & Co. is an American multinational investment banking and financial services company. Like other successful financial services businesses, Data Science is one of the reasons behind the success of JP Morgan Chase. So, if you want to…
A scatter plot is a data visualization technique to analyze relationships between two variables and find outliers. Understanding data visualization graphs is not easy for everyone. So if you want to know how to analyze a scatter plot, this article…
Zomato is an Indian restaurant aggregator and food delivery company. It is known for faster delivery of food from anywhere in your city. Like every successful business today, Data Science is one of the reasons behind the success of Zomato.…
Getting a Data Science job is hard for freshers without any work experience. So what should you do as a fresher? As a fresher, you can focus on entry-level job roles in Data Science to get experience. In this article,…
The Social Progress Index (SPI) is a measure that gives an understanding of social progress globally. It helps in understanding how much countries care about the overall development of the citizens. If you want to know how to analyze the…
Nykaa is one of the popular e-commerce platforms in India. It is known for beauty, wellness, and fashion products. Like every successful business today, Data Science is one of the reasons behind the success of Nykaa. So, if you want…
As a Data Science beginner, you need to work on various projects to get your desired job. Working on projects is valuable because your projects are the highlights of your resume when you are a fresher. Once you get experienced,…
Recommendation Systems are one of the popular applications of Data Science for every e-commerce platform. When it comes to fashion, an e-commerce platform wants to recommend the most trending fashion to its users for higher sales and engagement. Myntra is…
Spotify is an audio streaming platform with over 456 million monthly active users. Spotify is one of the best examples of companies that use Data Science and Machine Learning techniques to provide its services. So, if you want to know…
One of the reasons behind the success of many businesses is how they use the data generated by their business and customers in decision-making and improving their products and services. So, if you want to know how companies worldwide use…
A recommendation system is a popular application of Data Science that recommends personalized content based on the users’ interests. Almost all the popular websites you visit today use a recommendation system. As the name suggests, a job recommendation system is…
Paytm is a digital payments and financial services company. Just like other fintech companies, data is the ABC for Paytm. So, if you want to know how Paytm uses Data Science, this article is for you. In this article, I…
Youtube is a popular social media platform where we can upload videos to educate or entertain an audience of every kind. There are many areas where Youtube uses Data Science for its business and to provide a better user experience.…
Data Science is one of the highest-paying career options today. There are many jobs in the Data Science field you can prepare for as a fresher or an experienced professional. So, if you want to know about the highest-paying career…
Apple is one of the most loved tech brands worldwide. Most of the products of Apple are known for productivity, user experience, and privacy. There are many ways how Apple is using Data Science and Machine Learning in its products…
A Business Analyst is a Data Science professional who analyzes and forecasts business trends, understands and analyzes business strategies, and performs budgeting and financial analysis of the business. If you are aiming for the role of a Business Analyst and…
Every sports event generates a lot of data which we can use to analyze the performance of players, teams, and many highlights of the game. As the ICC Men’s T20 world cup has just finished, it has generated a lot…
Netflix is a subscription-based streaming platform that allows users to watch movies and TV shows without advertisements. One of the reasons behind the popularity of Netflix is the way Data Science is used at Netflix to improve its services as…
Data Science is one of the highest-paying career options today. But many freshers find it hard to get their first Data Science job. Companies need experience, freshers look for work to become experienced, and the loop continues. So how to…
A/B Testing means analyzing two marketing strategies to choose the best marketing strategy that can convert more traffic into sales (or more traffic into your desired goal) effectively and efficiently. A/B testing is one of the valuable concepts that every…
Grammarly is one of the best examples of applications that use Machine Learning for their business. Grammarly helps write a text for any purpose and uses Machine Learning to make that text more readable and engaging. So, if you want…
Data Science is one of the highest-paying career options today. Data Science is not like Engineering, where you need an engineering degree with a computer science background. Data Science is a skill that helps companies make decisions with data. So…
Twitter is one of the popular social media applications where people share what they feel in a limited number of words. Twitter is popular but not in the stock market. As Twitter is being delisted from the New York stock…
Like all other jobs, the salary of a Data Scientist also depends on many factors like work experience, living standards in the country, and the demand for Data Science professionals in the country. Out of all these factors, work experience…
Instagram is one of the most popular social media applications today. Just like every business today, there are many areas where Instagram uses Data Science. So, if you want to know how Instagram uses Data Science, this article is for…
Data Science is one of the highest-paying career options today. There are many free and paid platforms today where you can learn everything about Data Science. So, if you are looking for the platforms you should follow to learn Data…
Google is the most used search engine worldwide. One of the reasons behind the success of Google as a search engine is the way Google uses Data Science to improve its search results for every user. So, if you want…
Screen Time Analysis lets you know how much time you spend on what kind of applications and websites using your device. And screen time analysis gives a visual report of the same. So, if you want to learn how to…
A time series data is a sequence of data collected over an interval of time. When we work on time series data to analyze and find patterns, it is known as Time Series Analysis and forecasting. So, if you are looking for…
Amazon is one of the largest e-commerce platforms today. One of the reasons behind the success of Amazon is the way Amazon uses Data Science for its business. So, if you want to know how Amazon uses Data Science, this article is for…
Data Scientists and Data Analysts are Data Science professionals with some skills in common and different responsibilities. So, if you don’t know how a Data Scientist differs from a Data Analyst, this article is for you. In this article, I…
In Data Science, weather forecasting is an application of Time Series Forecasting where we use time-series data and algorithms to make forecasts for a given time. If you want to learn how to forecast the weather using your Data Science…
Kaggle is a Data Science community owned by Google. You will find thousands of datasets and case studies on Kaggle to improve your Data Science skills. So, if you are looking for some case studies to practice your Data Science…
Tinder is an online dating and geosocial platform. Many users find Tinder helpful for meeting new people for friendships and relationships. Just like every business today, Tinder also use Data Science for its business. So, if you want to know how Tinder uses…
Data Scientists and Data Engineers are Data Science professionals with some skills in common and different responsibilities. If you don’t know how a Data Scientist differs from a Data Engineer, this article is for you. In this article, I will…
Flipkart introduces a sale every year during the festive season in India. This sale is known as the Big Billion Days sale. The focus of the sale is on electronics of every kind, including flagship smartphones. So, if you want…
There are many tools Data Science professionals use daily to solve business problems with data. To become a Data Science professional, you need to learn all the necessary tools. So, if you want to know about the tools and software…
Uber is an American mobility-as-a-service provider that currently operates in 72 countries. Uber is also among the companies that use data and algorithms as a necessity for their business. So, if you want to know how Uber uses Data Science, this…
Data Scientists and Machine Learning Engineers are Data Science professionals with different skillset and responsibilities. So, if you are confused about how a Data Scientist differs from a Machine Learning Engineer, this article is for you. In this article, I…
A diamond is one of the most expensive stones. The price of diamonds varies irrespective of the size because of the factors affecting the price of a diamond. So, if you want to learn how to use your Data Science…
Data Science is the combination of data mining and computer science. As the use of data has increased in every domain, Data Science is one of the highest-paying career options today. If you want to learn Data Science and looking…
Apple iPhones are among the top-selling smartphones worldwide. There is huge competition among smartphone brands in India, where you can get the latest technology in a smartphone at half the price of an iPhone. Still, there are high sales of iPhones…
Instagram is one of the most popular social media apps today. It contains valuable features for both content creators and consumers. There are many areas where Instagram uses Data Science to make it more helpful to its users. So, if…
Data Science is one of the highest-paid career options today. If you want to learn Data Science, you don’t need to spend a lot as there are so many free resources on the internet to learn Data Science. So, if…
Business Forecasting is one of the popular applications of Data Science. In Business Forecasting, we use the data generated by the business to forecast the future sales, expenditure, or revenue of the company. If you are looking for some project…
Data Analysts and Business Analysts are Data Science professionals with different skillset and responsibilities. Both these professions are not completely different. So, if you are confused about how Business Analysts and Data Analysts are different, this article is for you.…
Business Forecasting is one of the applications of Time Series Forecasting. In Business Forecasting, we aim to forecast future sales, expenditure, or revenue by using the historical Time Series data generated by the business. So, if you want to learn…
A Business Analyst is a Data Science professional who uses the data generated by the business to analyze and forecast the performance of a business. If you are aiming for the role of a Business Analyst and want to know what…
MySQL is an open-source relational database management system. Knowing MySQL will always help you in your career in any field of computer science. So, if you are a MacBook user and want to know how to install MySQL on your…
Working on Data Science projects is one of the best ways to improve your Data Science skills. It not only boosts your skills but also strengthens your resume. So, if you are a Data Science beginner and want to know how to…
A Data Engineer is a Data Science professional who collects, transforms, and process data according to the need of the business. Data Engineering is one of the most in-demand Data Science jobs. So, if you are aiming for the position…
Data Science is a combination of data mining and computer science. It is one of the most in-demand career options in the industry. Still, many Data Science freshers struggle to get their first job as most companies look for experienced Data…
Statistics means collecting, organizing, analyzing, interpreting, and presenting data. Statistics is one of the most valuable concepts for Data Science. A person with statistical background is preferred for the role of a Data Science professional. So, if you are looking…
Social Media applications are those applications where you get a collection of features based on communication, interaction, content creation, and collaboration. Facebook, Instagram, Youtube, and Twitter are some of the popular social media applications today. Every social media application uses Data…
Data Analysis means analyzing data to gather valuable insights that can be used in decision-making and solving various business problems. Data Analysis is so popular that you can learn everything about it without spending any money. But some people like to…
E-commerce is nothing but the buying and selling of goods and services over the internet. Amazon is one of the most popular e-commerce platforms in the world. So, if you want to know how E-commerce platforms use Data Science, this…
Data Analysis means analyzing data to gather valuable insights that can be used in decision-making and solving various business problems. So, if you are looking for a step-by-step guide to learning Data Analysis, this article is for you. In this…
Astronomy is the study of everything we see with the naked eye or discover from the telescope, satellites and other instruments in the universe. The instruments used to study the universe collect data in many forms. Scientists use this data…
A recommendation system is one of the popular applications of Data Science. A Book Recommendation system is an application used to recommend similar books to a user. If you want to learn how to build a book recommendation system, this…
Fintech means using technology to provide financial services. There are a lot of Fintech companies we take any finance service from daily. Some worldwide known examples of Fintech companies are Mastercard, Visa, Stripe, and Paypal. Data is considered the ABCD…
Stock Market Analysis means analyzing the current and historical trends in the stock market to make future buying and selling decisions. Stock market analysis is one of the best use cases of Data Science in finance. So, if you want…
A Data Analyst analyzes data to gather valuable insights that can be used for decision-making and solving various business problems. The job of a Data Analyst can be different in every organization and every domain. But there are some responsibilities…
The activities a business performs to promote its products or services among the target population is known as Marketing. There are a lot of problems where Data Science is used in the marketing domain. So, if you want to know…
Data Analysis is the process of analyzing data to gather valuable insights that can be used for decision-making and solving various business problems. There are many tools that you can use for Data Analysis. In this article, I will take…
If you visit some of the LinkedIn profiles of Data Science professionals, you will notice that most of them don’t have a master’s or a bachelor’s degree in Data Science. Most of them have engineering or statistical background. They don’t…
Website Traffic Forecasting means forecasting traffic on a website during a particular period. It is one of the best use cases of Time Series Forecasting. If you want to learn how to forecast traffic on a website, this article is…
Data science is a combination of data mining and computer science. Data plays an important role in every data science task. As a data science professional, you need to know what kind of data you are working with to solve…
Time Series Forecasting is the process of analyzing and modeling time-series data. It helps in forecasting the future behaviour of the market, which is helpful in the decision-making for every business. Some of the applications of Time Series Forecasting are…
Time Series Forecasting means analyzing and modeling time-series data to make future decisions. Some of the applications of Time Series Forecasting are weather forecasting, sales forecasting, business forecasting, stock price forecasting, etc. The ARIMA model is a popular statistical technique…
Salary is one of the most valuable factors in choosing a career. No one would like to prepare for a job that doesn’t pay well. So, if you are preparing for the role of a Data Science professional and want…
Data science is one of the highest paying career options today. There are many jobs in this field, some of the most popular of which are Data Scientist, Data Analyst, Data Engineer, and Machine Learning Engineer. If you know you…
Seaborn is one of the best Python libraries for Data Visualization. It is built on top of Matplotlib. Unlike Matplotlib, Seaborn cannot be the only Data Visualization library in your skillset, but some visualizations look better and more understandable with…
The new MacBooks with the M1 processor provide so many specifications that are enough for every Data Science and Machine Learning professional. But if you have just purchased a MacBook, you have to create a virtual environment to prepare it…
There is a lot of competition among the brands in the smartwatch industry. Smartwatches are preferred by people who like to take care of their fitness. Analyzing the data collected on your fitness is one of the use cases of…
Working on a data science project is one of the best ways of showing your skills in working with data. If you are a data science student, your university will ask you to submit a report on your data science project in…
Sentiment analysis of reviews of a product or service helps businesses understand what their customers want from them. Analyzing the reviews is one of the primary use cases for sentiment analysis. If you’re looking for data science projects on sentiment…
One of the tasks while solving a machine learning problem using Python is to convert a Pandas DataFrame to a NumPy array. A pandas DataFrame is a DataFrame object that we use to work with data, and a NumPy array…
Data Science is one of the highest-paid career options today. It is so popular that you can learn everything about data science without spending any money. But some people like to choose a paid course over free resources as we…
Data Analysis is the process of analyzing a large amount of data to find relationships between different features in the data. If you are a final year student of business analysis or data analysis and looking for some data analysis…
Analyzing a player’s performance is one of the use cases of Data Science in sports analytics. Virat Kohli is one of the most famous cricketers in the world. So it will be a great data science project if we analyze…
As a Data Science Professional, it is valuable to learn about using cloud computing platforms like Google Cloud Platform (GCP) or Amazon Web Services (AWS) for Data Science. So if you want to know how to learn Google Cloud Platform…
In Machine Learning, we use data and algorithms to build intelligent systems. If you are new to machine learning and looking for a certification or course to learn and get certified in machine learning, this article is for you. In…
Sports Analytics is the task of analyzing sports data. It includes player performance analysis, analysis of all game highlights, data storytelling and summary of a sports tournament, comparison of strengths and weaknesses of teams and players, etc. So, if you’re…
Every sporting event today generates a lot of data about the game, which is used to analyze the performance of players, teams, and every event of the game. So the use of data science is in every sport today. Currently,…
As a data science professional, it is important to learn how to use cloud computing platforms like Amazon Web Services or Google Cloud Platform for data science. So, if you want to know how to learn Amazon Web Services for…
As a beginner in data science, the choice of topics for data science projects depends on the ease of availability of datasets. Sometimes students think about unique topics, but they can’t find a dataset for their project. So if you…
Data Science is one of the best career options in this data-driven world. There are a lot of technical skills required to work as a data science professional in any domain. If you are learning Data Science and are looking…
Power BI is a data visualization tool from Microsoft. It lets us easily connect to data and visualize it to discover necessary insights. As a data science professional, you must know Power BI or Tableau. So, if you are looking…
Data analysis means working with data to gather the information which can be used for decision making and solving various business problems. There are many free resources on the internet for learning data analysis. But if you are looking for…
The use of data science is in all fields today. Economics is one of the fields in which we study the growth of a country by understanding the data on the economic factors of a Country. So, if you want…
The outbreak of Covid-19 resulted in a lot of restrictions which resulted in so many impacts on the global economy. Almost all the countries were impacted negatively by the rise in the cases of Covid-19. If you want to learn…
Tableau is one of the most popular data science tools used for data visualization and analysis. If you want to become a data scientist, you need to know how to use Tableau. So if you’re looking for some of the…
Data Science certifications are all about certifying whether a person knows how to work with data or not. Although if you have a good list of projects in your portfolio, you don’t need any data science certification. Having a certification…
Many beginners in data science are often confused about what job role they should prepare for. People who are starting to learn data science have either an engineering background, a statistical background, or a non-computer background. Each person has their…
Many data science beginners can solve any data science problem by following a tutorial, but they often struggle to solve a new data science problem. It’s not easy for beginners to start solving a problem when they see a new…
SQL is one of the most important skills for data science professionals. Most data science beginners don’t focus on learning SQL as much as on learning Python. SQL is as important as Python for data science, especially if you’re looking…
Matplotlib is one of the most preferred Python libraries for data visualization. If you are learning data science, you must be aware of the kinds of data visualizations you need to work with. In this article, I will not focus…