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Data Science

Tools covered in MAHE’s M.Sc. in Data Science

Admin | September 19, 2022

Key takeaways:

  • Data science is the use of tools and techniques to find patterns and meaning in data. 
  • Data science can help you with anything from making your business more efficient to help you understand how your customers are using your products.
  • Manipal Academy of Higher Education’s (MAHE) M.Sc. in data science covers tools like Python, R, SQL, Tenserflow, Weka and many more.
  • If you want to make beautiful visualizations with your data, then Plotly is our recommendation for creating interactive graphics with Python and R scripts (among other languages).

Manipal Academy of Higher Education’s (MAHE) M.Sc. in Data Science is a comprehensive course covering some essential python tools used in data science today. It is designed to give you a firm foundation in statistics, machine learning, artificial intelligence, and deep learning while exposing you to the latest developments in data science research.

The program will help you develop critical thinking skills essential for any successful career in data science or related fields. In addition to learning data interpretation and the discovery of patterns within it, you will learn about the use of machine learning algorithms for prediction and classification of tasks and the use of AI techniques for problem-solving.

This article will examine some of the most critical data science tools covered in MAHE’s M.Sc. in data science. We will also discuss how they are used in data science applications and why they are essential to learn when you begin your career as a data scientist.

What is an online M.Sc. in Data Science?

Online M.Sc. in data science is a multidisciplinary course designed by MAHE that helps you acquire expertise in data science. If you are looking for a career in data science, an online master’s program with Online Manipal can help you get the training and credentials you need to succeed in the field.

Here’s what you need to know about online M.Sc. in data science – 

  • Interdisciplinary expertise

Data science is a cross-disciplinary field requiring expertise from various areas, including computer science, mathematics, statistics, and information technology. The online M.Sc. in data science is designed to give you a well-rounded understanding of these fields to apply the principles learned in your studies to real-world problems.

  • Strong academic support

MAHE’s online M.Sc. in data science program has a dedicated team of academic advisers available to help you stay on track with your studies, be it providing guidance in choosing courses or helping you navigate the admissions process. They will help in clarifying doubts about your coursework and future career prospects after graduation.

  • Self-paced learning

The program is designed for professionals who need flexibility in their schedules. But it doesn’t mean you will be sacrificing on quality. We offer classes every month and provide access to a wealth of resources that will guide you through each step of the program so that you can graduate sooner than expected without sacrificing quality education or personalised attention from your instructors.

  • Industry-oriented curriculum

M.Sc. in data science is an online degree designed to equip you with the skills and knowledge required to pursue a career in the competitive field. The coursework is industry-oriented, which means that it covers the key topics that are most relevant to your career goals.

  • Better job opportunities 

Data science is one of the fastest-growing fields, and an M.Sc. in data science can help you get there by providing you with the skills needed to work in analytical or leadership roles within the field.

  • Enhanced problem-solving skills

M.Sc. in data science allows you to enhance your problem-solving skills by learning to use data effectively, interpret results, and identify patterns using statistical methods like regression analysis, correlation tests, time series analysis, etc.

What types of tools does a data science practitioner use?

Data analysis toolsVisualisation toolsData cleaning toolsData exploration tools

Data scientists use various data science tools to perform their tasks, and the list is constantly growing. However, some data science tools are used more often than others.

  • Data analysis tools

Data analysis tools help you organize and clean your data and perform calculations on it. These tools can help you identify patterns in your data, find correlations between different variables, and more. Some common examples include RStudio and Python’s Pandas package.

  • Visualization tools

Visualization tools help you turn your data into something visual, like graphs or charts. These visualization tools are excellent for communicating information quickly and clearly to others. They allow people who haven’t spent time analyzing your data to quickly grasp what it means by looking at it. Some common examples include Tableau Public, Plotly, and Google Sheets’ charting tool.

  • Data cleaning tools

Data cleaning tools are used to get rid of any errors and discrepancies in your data set before you begin your analysis. This ensures that your results are as accurate as possible.

  • Data exploration tools

Data exploration tools help you understand the relationship between variables within your dataset. These tools in data science allow you to explore data in different ways, such as through heatmaps or scatterplots, which can help you see if there are any outliers or other issues with the data.

Tools covered in online M.Sc. in data science

Here are some of the most common tools covered in an M.Sc in data science:

  • Hadoop

Hadoop is a software framework that allows data to be distributed across a network of computers. It is used to store large amounts of unstructured data and can also be used for machine learning and other types of data analysis.

  • Colab

Colab is a cloud-based data science tool that allows you to write and run code in the cloud. It is a great way to start coding without downloading any software or setting up your own computer.

  • Apache Hive

Apache Hive is an open-source SQL-like query language for analyzing big data sets stored in Hadoop. It allows users to manipulate large datasets without writing complex MapReduce jobs by hand.

  • KNIME

KNIME is a data science platform that allows you to quickly and easily access the tools you need to run your analysis. It is open source, meaning it is free to use and easy to install. With KNIME, you can create workflows that automate your data science tasks—from loading data into the platform to running analysis. You can also use KNIME to share your workflows with others in your organization or study group.

  • Matplotlib

Matplotlib is a Python library for creating graphs and visualizations with minimal code. If you want to produce high-quality graphs without learning another tool, then Matplotlib is the one for you.

  • NumPy

NumPy is a Python library for scientific computing. It provides fast array operations and functions designed for numerical computing. If you are new to Python and science, then NumPy will make it easy for you to get started with some of their best features in one place.

  • OpenCV

OpenCV is an open-source library for computer vision. It can be used to detect and recognize faces, cars, traffic signs, and much more. It’s also used in applications like self-driving cars and medical imaging.

  • Pandas

Pandas is a Python library for data analysis. It provides easy-to-use functions for manipulating structured data in tables, such as reading and writing files from Excel or Google Sheets. It also makes it easy to group your data into groups or columns based on the values in those columns.

  • Python

Python is a programming language used by many tech companies including Google, Facebook, LinkedIn, Dropbox, Spotify, Netflix, and more. It’s also one of the most popular languages among data scientists due to its ease of use.

  • R

R is an open-source programming language that is widely used in data science. It is flexible, powerful, and easy to learn, so it is ideal for beginners. R is primarily used for statistical analysis and visualizations like graphs and charts.

  • SAS

SAS is a proprietary software program used for business intelligence and analytics. It allows users to quickly perform complex calculations on large amounts of data, making it ideal for significant businesses that need to analyze their data efficiently.

  • Spark

Spark is a cluster computing framework designed specifically for big data processing tasks. It works by distributing tasks across multiple servers, making it faster than traditional methods such as MapReduce or Hive. Each server only needs to handle part of the workload at once instead of all of it (which would require more servers).

  • SPSS

SPSS is a statistical software used to analyze, manage and manipulate data. It is an essential tool used in data science for anyone who wishes to have a career in data science.

  • SQL

Structured Query Language (SQL) is a programming language for managing data in relational database management systems (RDBMS). SQL is one of the world’s most widely used programming languages, with some estimates placing a high number of businesses using it.

  • TensorFlow

TensorFlow is a machine-learning software library created by members of the Google Brain team. It can be used to build neural networks and deep learning applications. It provides a flexible architecture that allows you to deploy computation on one or more CPUs or GPUs in a desktop, server, or mobile device with just a few lines of code.

  • WEKA

Weka (Waikato Environment for Knowledge Analysis) is an open-source software library written in Java that provides data mining tools. Weka contains tools for data pre-processing, classification, regression analysis, clustering, and feature selection.

Learn data science tools with Online Manipal

Online Manipal does not merely focus on teaching you how to use a tool, but also shows you how it is used in the real-world and its applications in different industries. The courses offered by MAHE on the Online Manipal platform are designed for all learners from all levels, from beginners to advanced, catering to the needs of both freshers and experienced professionals.

Closing

The demand for data scientists is skyrocketing, and companies are willing to pay more. If you want to be part of the next generation of workers who will drive innovation in the 21st century, then learning data science is a great way to get started.

By enrolling for MAHE’s M.Sc. in Data Science with Online Manipal, you can learn from the comfort of your home and at your own pace, and learn from industry experts.

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