Softenant Technologies offers Best Data Science Training in Vizag. Data Science is the most demand course in the market. It is mainly used for predictive analysis. There are many companies has got huge data for analyzing the latest problems. To solve much challenging data science is very helpful.

For solving industry problems data analytics are in huge demand. We at Softenant Technologies provide basic to an advanced course on data analytics.

Who should take the Data Science course in Vizag at Softenant?

  • Professionals already having worked on any domain.

  • Mathematicians, Statisticians, and Economists

  • Business analysts, Software Programmers, Business Intelligence persons.

  • Freshers having good logical and analytical skills.

Data Science Course Modules

SQL

  • DDL, DML, DCL

  • Index in RDBMS

  • Clauses in SQL

  • Operators in SQL

  • Creating Database

  • SQL Functions

  • Triggers in SQL

R-Programming

  • Data Structures in R

  • Variables

  • Operators

  • Conditional Statements

  • Loops

  • Strings

  • Functions

  • Statistical programming

  • Bar charts, Pie chart, Line Chart

  • Pareto chart, Histogram, Scatterplot

  • Import Dataset in R

  • Reading various files

  • CSV files, SAS files, JSON files, Text files

  • Packages

  • Hmisc

  • Caret

  • Data Table

  • Ggplot2

  • Dplyr

Python

  • Data Types

  • Conditional Statements

  • Loop

  • Functions

  • Numpy in Python

  • Reshaping and combining Arrays

  • Arrays

  • Pandas

  • Introduction

  • Dataframe

  • Working with Missing Data

  • Merge, Join and Concatenate

  • Indexing and Selecting Data

MatplotLib Library in Python

  • Introduction

  • Design

  • Different visualizations

Scipy and Sklearn in Python

  • Installations

  • Scipy Introduction

  • Mathematical algorithms

  • Sklearn

  • Machine Learning Algorithms

Seaborn Library in Python

  • Introduction to seaborn library

  • Linear relationships

  • Statistical relationships

  • Plotting Categorical Data

  • Statistical Analysis

  • A high-level overview of Data Science

  • Random variable

  • Probability and Distribution

  • Balanced and Imbalanced datasets

  • Sampling Funnel

  • The measure of central tendency

  • Measure of Dispersion

Regressions

  • Linear Regression

  • Logistic Regression

  • Multinomial Regression

  • Advanced Regression

Clustering

  • Unsupervised Data Mining

  • Dimension Reduction

  • KNN Machine Learning Classifiers

  • Data Visualization

  • Time Series

Tableau Products and Usage

  • Maps and Images in Tableau

  • Calculation On Tableau

  • Data Collection

  • Data Mining

What is Data Science Course and its Benefits?

As we are entering into the era of new technologies and big data, the demand for storing the data is also increasing. Therefore, you must know what is Data Science and its Benefits. One of the main challenges of large enterprises until 2010, was how to store such a huge amount of data.

Their main objective was on building the framework and finding the solution to store data. After the introduction of Hadoop, the problem of storage was completely solved but the new problem arises. The problem was how to process the data.

Data Science has evolved as a solution to this problem. Whatever you watch in science fiction movies can actually turn true with the help of Data Science. It is the future of Artificial Intelligence. Hence, it becomes very important to understand what is Data Science and its benefits?

What is Data Science?

The use of Data Science is very common between us, but what does it mean? How can you become a Data Scientist? And what are the technologies used in making predictions?

Data Science is a combination of tools, algorithms, and principles used in Machine Learning. It is used to locate the hidden patterns from raw data. The role of the Data Analyst is to explain and figure out the processing history of data. Moreover, they not only do the exploratory analysis to discover the insights but also use various machine learning algorithms to find out the occurrence of any event in the future. Their objective is to view the data from different angles and predict the correct outcome.

The lifecycle of Data Science

The lifecycle of Data Science is divided into 6 phases-

  • Discovery

Before starting any project, it is necessary to understand the various specifications, requirements, and priorities it requires. You need to answer the correct questions. You should be sure enough to have the required resources in terms of people, technology, and time. In this phase, you are required to frame the business problem and plan the initial hypothesis (IH) to test.

  • Data Preparation

This phase requires the analytical sandbox in which you can perform the analytics related to the project. You are required to explore and preprocess the data prior to modeling. After that, you need to perform ETLT (extract, transform, and transform) to get the data into the sandbox. For data cleaning and visualization, you can use R. It will help in building a relationship between the variables.

  • Model Planning

In this phase, you will decide the techniques used to build a relationship between the variables. These will act as a foundation for all the algorithms which you will implement in the next phase. You need to apply Exploratory Data Analytics (EDA) using various statistical formulas.

  • Model Building

This phase requires to develop datasets for the purpose of training and testing. Here, you will get to know whether your tools will serve for running the models or require a more robust environment. You will also learn various techniques such as classification, association, and clustering to grow the model.

  • Operationalize

You will deliver all the final reports, briefings, and technical documentation in this phase. Sometimes you are required to submit a pilot project in the real-time production environment. With this, you will get a clear picture of all performances on a small scale before full deployment.


  • Communicate results

This is the final phase where you need to evaluate whether you have reached your goal, planned in the first phase. Here, you need to point out all the key findings, talk to different stakeholders, and then decide whether the results of the project are successful or a failure depending upon the criteria decided in Phase 1.

Why Should You Become a Data Scientist?

According to Glassdoor, the job of Data Scientist is ranked as #1 for the year 2018. The continuous increase in the data requires more scientists to handle it effectively and accurately. In the upcoming years, the need for data scientists will grow exponentially to overcome its usage. It is estimated that around 2021, the increase in demand for data scientists can be increased by 28% with the number of 4530 job openings, and an average base salary of up to $120,931.

Advantages of Data Science

It has been proved by several researchers that most of the businesses can be extremely benefited with the correct use of data analytics to get positive results. There has been a huge role of Data Science in further expanding and improving several aspects of the business. Apart from this, let us see what are the other benefits, Data Science can offer us-

  • Redefined customer success

You must have already heard that several data are being used in identifying different opportunities, modifying strategies, or designing campaigns. But sometimes the predictive power of data can benefit you in those fields where you didn’t expect to. There are times when information lies in data beyond what businesses can think. The data-driven companies usually depend on the performance of their audience to determine the market and maximize the results. In such cases, the actual insights of data can help to get more customer attributes to be leveraged.

  • Agriculture Sector

The agriculture sector is another field that can take huge benefits from Data Science technology. With the correct use of it, the farmers can decide the right amount of fertilizers and water required to grow the crop. They can also gain knowledge of planting the right amount of seeds to take out the maximum benefits. They will also get to know about the weather forecast beforehand so that they can plan the crops accordingly.

  • Journalism

“Data-Driven Journalism” or “Data Journalism”, you must have some knowledge about these terms. If not, this field is considered to get the best-unexpected data science benefits. The whole concept of journalism and its related jobs can highly be influenced through data analysis and visualization. This approach can be used to evaluate the performance of the journalists based on likes, CTR, and shares on social media. This can boost them in targeting the correct reports in newspapers or magazines.

  • Education Sector

The use of Data Science in the Education sector can sound a bit unusual to many people. But the truth is, most of the institutes are now set to analyze the students with the help of analytic insights. Moreover, there are institutes that not only use the analytics but also develop marketing strategies with the help of Data Science to attract a large number of eligible students. The right execution of Data Science has allowed them to make better decisions in the admissions of potential students.

  • Airline Industry

One of the staggering data science benefits can be seen in the airline industry. This is the only industry that has experienced heavy losses due to COVID-19. Except few, most of them are still struggling to manage their profits and occupancy ratio. Due to the increase in fuel prices, the situation has got worse. Data Science technology can actually help in improving this condition by predicting the time of flight delay, deciding the class of airplanes, and predicting whether the flight should reach the destination directly or via multiple halts.

  • Image and Speech Recognition

You must be not familiar with this topic, but you will not believe data science is strongly involved here and you use it every day. The best example of this is whenever you upload any picture and start tagging your friends. You must have noticed that while doing this, you get an automatic recommendation of your friend’s profile. This is the best example of the image recognition technique.

The best examples of speech recognition are Google Voice, Cortana, Siri, etc. Speech Recognition makes the work easier by not allowing you to type the commands. You need to just speak and it will directly convert your voice into text. The best use of Data Science can be seen here.

  • Healthcare Industry

In the healthcare industry, Data Science can be used to predict the patient’s admission rates which help the doctors to accurately measure all the patients. Through Data Science, they can easily diagnose the patients quickly and more accurately. Therefore, it plays an important role in saving lives. All the applications and wearables that monitor the patients on a constant basis is done with the help of data analytics and helps in preventing potential health problems. Also, the Machine Learning algorithms that are used in medical science can be used to analyze the biological samples from patients to cure them.

Conclusion

I believe you must have got the answer to what is data science and its benefits. The above-mentioned fields ar e just some of the benefits of Data Science. Apart from this, there are a lot of other sectors where Data Science is gradually growing. And till now, if you have not utilized this field, then it is the best time to do so. Since all the businesses are now getting converted to digital platforms, therefore, they are flooded with lots of data. And it is important for them to hire DataScience Professionals, hence it is a highly demanded field across all industries.

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