Data Science Training

What is the need of Data Science for the Companies?

Decision Management – Data scientists holds the advantage of high responsibility on making the right decisions on all the aspects of an organization.The Decision making involves the analysing, measuring the data metrics.Data Scientist are the ones who are helping the management to take actionable and right decisions for the growth of company

Updated Strategies – Data Scientist would collect and analyse the data frequently, which would be kept in action by the organization on immediate, this would help the organisations to take a note on their long term and short term goals

Operational Efficiency : Data Scientist would help to improve the manufacturing operations efficiency by transforming the whole process into big data.

What is the Need to learn Data Science ?

Job Demand : The Data Scientist jobs are booming at rapid pace, in a decade we can expect at least quarter of the IT market would be flooded with Data Science Jobs.Every Company is now looking for people who can analyse the data and give some actionable insights to grow the company profits.

Career Improvement and Perks : Data Scientist are full of shortage on all the levels between manager and entry level, one can expect that most people would prefer to choose the data science as their domain, in return the career stagnation would become less.

Data Scientist Salary : The Data Scientist would earn on an average of more than 50% of the Normal IT Employees

What Can you learn in our Data Science Course ?

Data Science Specialization Training

Hope Tutors provides one of the best data science educations through the Experienced Data Science Trainers in Chennai.We provide the teaching on data science specialization topics that would help you to learn the basics and get tuned for the projects easier.

Data-Driven Decision Training

We Focus on the Applications more than theory as it would help you to tackle some real time data challenges faced by data scientists nowadays with a pool of data science tools and techniques

Data Science Essentials Training

We knows that students need to have some basic knowledge on data science tools like python and R, so we updated the course that include probability, data exploration and visualization.

Intro to Machine Learning

We also cover the concepts like machine learning which is the hottest trending choice among the data scientist.

What are the tools that cover in Data Science ?

We are not forced to use any tool, as there is no standardisation on the tools that can be implemented for the Data Science, I covered some of the most tools used based on the approach they would take on the data.

Data Analysis

R Language

The R language is mostly used among the data miners on developing any analytical software and data analysis.It is easy to use and the tools extensibility has raised people to use it as primary for their data analysis.It also provides the graphical and statistical techniques like linear and nonlinear modeling, clustering and others.

Data Warehousing

• MySQL: MySQL is the tool that is used to access the data from database.It can easily handle the datasets that are limited upto 50-100 million records
• Hive/Shark/Redshift: If you are using the loads of data, you can fo for the amazon redshift/shark/hive. They are well suited for latency but limited in their joins.

Data Visualization Tools

Tableau : Tableau is the most used tool as it provides the easy drag and drop interface.It is multiformat supported and also available in free version for some basic features.

SAS Visual Analytics : SAS VA is a data visualization tool that can be capable on doing the predictive modeling and forecasting.It also supports drag and drop interface, with some great community support.

Data Extraction Tools

Content Grabber : Content Grabber is the web crawler that is targeted for the business professionals.IT would extract the content from any website and would give in a structured format of your choice.It suits the people who possess the advanced programming skills as it offers the debugging and script editing features.

Parsehub : Parsehub is the web crawler capable of collection of the data from the websites that was made of Ajax,JS etc. It can read, analyze and then transform the whole web documents into useful and relevant data. It offers both free and premium packages.

Machine Learning Algorithms

For getting the organization to work efficiently, we need some scalable and efficient modeling strategies.The Models is the implementation of the algorithms which leads to the business growth

Supervised vs Unsupervised learning models

The Supervised learning is the mathematical models where there is a clear difference between the explanatory and dependent variables. The Dependent variables are known beforehand.

• Prediction
• Classification
• Time‐series forecasting

There is no target attributes in the unsupervised learning, as there is no difference between the explanatory and dependent variables.

• Association rules
• Cluster analysis

I explained the top Machine Learning Algorithms that will be useful for the data science course.

1. Hypothesis Testing

The Hypothesis testing is the procedure on statistical tests which are used to check the hypothesis true or not. It is mainly used to find out the event occurrence, to know whether it is is a trend or happened by chance, the hypothesis testing is necessary Based on hypothetical testing, we choose to accept or reject the hypothesis.

2. Linear Regression

Linear regression is the statistical modelling type of strategy which would help to model the difference between explanatory and dependent variable by the help of linear equation.

3. Logistic Regression

Logistic regression is the modelling strategy to know the difference of the input and output variables, the only difference with the linear regressions is the output would be an binary outcome

4. Clustering

Clustering is the algorithm which is unsupervised as the output has not been known to the analyst.The Algorithm do not have any past inputs so that the outputs would be vary. There is no right solution to the clustering, the best way to use them was implementing them on business usability.

5. ANOVA

The ANOVA test is the technique that applied to the mean of two or more data sets which is insignificant to each other.The comparison of the variance between two groups to within group variance is the ANOV Working model.

6. Principal Component Analysis

The Principal Component Analysis was measuring the data on the idea of principal component. The largest variance would be the the major principal component dataset. The PCA analysis is involving the each variable axis rotation to highest eigenvalue and getting the principal components

7. Conjoint Analysis

Conjoint analysis is the technique that is used for the identification of customers choices on the most attributes like price,color and size. It is used by brand managers which would be helpfu in building the brand reputation

Who should take this Data Science Course?

• Working professionals who are working on Big Data and Business Intelligence
• Machine Learning Working professionals
• Predictive Analytics Information Architects

What are the prerequisites for learning Data Science?

There are no particular prerequisites for this Training Course. If you are interested in maths, it would be great

What is the Job Description for Data Scientist ?

Data Scientist is data analyst who is applying the business intelligence for the company growth, it requires the maths and analytical skills to get the required insights and need to deliver to the company.

They are not relying on the traditional data analysis, they would collect the data from multiple sources and get the insights which would develop the organisation growth.They will work on the emotional intelligence which would help in their customer acquisition.

They should be good in analysing data using the tools,learning python language is appreciable.Learn some Data Science Interview Questions from us.

What is the Data Science Salary Trends ?

The average pay for Data Scientist is Rs 1,266,899 per year.