Data Science jobs are in high demand. According to Forbes, Data Scientist is one of the hottest professions predicted to rise by 28%. India Today mentions that the country will have more than 11 million job openings in Data Science by 2026. Since 2019, hiring in the Data Science industry has increased by 46%. Yet, around 93,000 jobs were vacant at the end of August 2020 in India. It creates the perfect opportunity to learn a skill that is in great demand.
To make your mark in the data-driven industry, register for the Data Science Course in Bhubaneswar. Learn interdisciplinary skills and know-how to handle and analyze large amounts of data for the most exciting career path.
Virtually every organization works with humongous data and looks for ways to use it to help them grow their business. That’s where Data Scientists come in. They apply their knowledge to uncover solutions hidden in the data to take on business challenges.
A Data Science major like the course at Bhubaneswar can help you become a Data Scientist skilled in statistics and computer science, with hands-on exposure to techniques and a capstone project designed to reinforce your learning in a real-world problem.
Before you can help your organization on a Data Science project, you must understand what Data Science is.
Data Science is the art of uncovering the insights and trends in data using sophisticated tools and technologies and applying statistical techniques and mathematics.
Unlike traditional data analytics, Data Science aims to delve beyond insight discovery to make decisions and predictions. The job of a Data Scientist is to use techniques like predictive and prescriptive analytics and machine learning algorithms to make sense of both structured and unstructured data.
Data Science training teaches you the necessary technical skills for success in this field. E-learning helps to hone your skills and strengthen your formal learning.
Whether you are working in IT or have an interest in entering the field, Data Science training will help you build a foundation in the discipline. Once you have gained the foundational skills for Data Science, you build on those skills with projects to generate more business value.
A Data Science Project is an industry project that solves a real-world problem.
You begin with
As a Data Science newbie, once you have a grasp of theoretical knowledge and navigated the learning path successfully, you must work on some real-world projects. It makes you industry-ready, besides looking good on your portfolio and helping your interviewer know your skill sets.
Chatbots are in great demand. From educational institutes to eCommerce, banking, and more, most organizations have a chatbot as a customer interface on their websites. Chatbots handle customer or website visitor queries without any slowdown. They reduce the workload of customer service departments and even help to turn a casual visitor into a customer.
Chatbots analyze the input from the customer and answer with an appropriate mapped response from a list of vocabulary, common sentences in use, and suitable responses using Natural Language Processing. You can train a Chatbot using Recurrent Neural Networks with the intents JSON dataset with Python handling the implementation.
Design ‘open-domain chatbots that handle extensive lists of generic type queries or ‘domain-specific chatbots to solve a particular type of problem specific to the business domain.
You can design a handwritten digit & character recognition project using the MNIST dataset of handwritten digits and Convolutional Neural Network to implement the project. For real-time prediction, you can build a graphical user interface to draw digits on a canvas for the model to predict the handwritten digit.
Credit card frauds are very common but can be intercepted using AI, ML, and Data Science. Customer’s credit card transactions and their locations are mapped to identify fraudulent transactions from non-fraudulent ones. This project uses R or Python, with the customer’s transaction history as the dataset, and ingests it into decision trees, Artificial Neural Networks, and Logistic Regression.
Media platforms like YouTube and Netflix use the recommender system to recommend what to watch next. Several metrics are considered, such as the previously watched shows, most-watched genre, watch frequency. Feeds them into a Machine Learning model to generate what the user may like to watch next. Based on the input data you can build a content-based recommendation system or a collaborative filtering recommendation system. Use R language with the MovieLens dataset for implementation.
Speech is a verbal expression that hides many emotions within it, like anger, joy, or agitation. By analyzing the speech, emotions can be identified and extracted from multiple sound files containing human speech. The information can be used to restructure services. You can make this project in Python, using the Ryerson Audio-Visual Database of Emotional Speech and Song(RAVDESS) dataset.
Forest fires and wildfires are making news in India and abroad. You can now build a forest fire prediction system using k-means clustering to identify fire hotspots and their intensity. This can be used to allocate resources and take timely actions.
The Data Science field may be new, but is growing rapidly. It is not enough to take a static approach to Data Science learning—you want a continuous approach to your education to maintain a competitive advantage in the job market.
These projects just scratch the surface of what you can do in Data Science. They make a great point to kickstart your Data Science journey and build a project portfolio to complement your resume.
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