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Best Institutes for Data Analytics training in Karnataka with Course Fees

List of 1+ Data Analytics training institutes located near to you in Karnataka as on August 24, 2019. Get access to training curriculum, placement training, course fees, contact phone numbers and students reviews.

 

 

training institutes IIHT Chikkamagaluru
Karnataka - Chikmagalur
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training institute
Address: Door No 22, Siddarameshwara Marga, 2nd Cross, Kalyan Nagar(Bypass Road) Chikmagalur Karnataka-577102

 
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Data Analytics Training Institutes in Karnataka - by Location

Yet5.com Provides complete list of best Data Analytics training institutes in Karnataka and training centers with contact address, phone number, training reviews, course fees, job placement, course content, special offers and trainer profile information by area.

 


 

 

 

Learning Data Analytics course in Karnataka - Benefits, Advantages & Placements.

We have identified the benefits of learning data-analytics course in Karnataka.
Data Analytics training in Karnataka is part of Bigdata training course class, Data Analytics is the science of analyzing data to convert the obtained information to useful knowledge
or it is the science of drawing insights from some source of information. It refers to quantitative as well as qualitative techniques used for improving the business gain. Data is extracted and categorized to identify and analyze the behavioral data and patterns, and techniques vary according to organizational requirements.

Data analytics program is mainly conducted in business-to-consumer applications. Global organizations will collect and analyze data associated with customers, business processes, market economics or practical experience. He/she who conducts this process are called as data analyst. Their responsibility is to generate insights from data and present it to stakeholders such as external or internal clients.
They first clean it up to prepare it for analysis. Later data analysis step involves exploration of data with descriptive statistics and then building predictive model for prediction. A Data analyst must know basics and intermediary statistics and know how to apply it with SAS / SPSS. The popular tools used in data analytics are excel and sql. so candidate must possess a good knowledge of these tools

Karnataka is located in the south western region of India with Bangalore as its capital. Karnataka has a literacy rate of 75.60%. Karnataka is home to some of the premier educational and research institutions of India such as the Indian Institute of Science, the IIM, the Indian Institute of Technology Dharwad the National Institute of Mental Health and Neurosciences, the NIT Karnataka and the National Law School of India University. Also, it is home to the famous universities such as Bangalore University, Gulbarga University, Karnatak University, Kuvempu University, Mangalore University and Mysore University with 481 degree colleges that are affiliated to one of these universities. There are 186 engineering, 39 medical and 41 dental colleges in Karnataka. As Bangalore is the Silicon Valley of India, a large number of IT companies such as Cognizant, Infosys, Wipro, TCS Accenture, HCL, Capgemini etc are located here that provide immense job opportunities to students all over India.
You have travel connectivity to data-analytics course educational training institutes in Karnataka. Karnataka has airports at Bengaluru, Mangalore, Belgaum, Hubli, Hampi, Bellary and Mysore for domestic flights, and international flights from Bangalore and Mangalore airports. Karnataka has an excellent Railway transportation system that covers all the cities of Karnataka and other states of India. Karnataka offers 1 major port and 10 minor ports as a part of its water transportation. KSRTC manages the public buses in Karnataka. Omni bus, Taxi cabs, autos and rickshaws are other common modes of road transport for inter city and intra city commuting.

 

 

 

Data Analytics course Content / syllabus in karnataka

Below is the Data Analytics course content in karnataka used by the training institutes as part of the Data Analytics course training. The Data Analytics course syllabus covers basic to advanced level course contents which is used by most of Data Analytics training classes in karnataka .

 

Introduction to Data Management

1.1 Language of Data Analytics
Learn tools and languages used for data analysis - R, Excel, SQL, Python & Tableau.These modules are also part of preparatory course

1.2 Introduction to Data Warehousing and OLAP
Equip yourself with the knowledge to extract and pre-process data before analysis

1.3 Data Preperation
Learn how to prepare data before you analyse them

1.4 Case Study- Investments
Implement your learnings to find sectors in which different companies ought to invest


2 Statistics and EDA

2.1 Data Visualization
Make your data alive with visuals using R and tools like Tableau

2.2 Descriptive Statistics
Summarize and describe data sets using a measures such as Central tendency and variability

2.3 Inferential Statistics
Learn probability, Central Limit Theorem and much more to draw inferences

2.4 Exploratory Data Analysis
Derive initial insights from the data using R and other visualization tools

2.5 Hypothesis Testing
Understand how to formulate & test hypotheses to solve various business problems

2.6 Case Study- Uber Supply Demand Gap
Apply Statistics and understand how you can solve the supply-demand gap of Uber cabs


3 Introduction to Predictive Analysis I

3.1 Linear Regression
Learn to implement linear regression and predict continuous data values

3.2 Supervised Classification
Understand and implement algorithms like K-NN*, Naive Bayes and Logistic Regression

3.3 Clustering
Learn how to create segments based on similarities using K-Means and Hierarchical clustering

3.4 Case Study - Telecom Churn
Help a telecom giant predict if a customer will churn or not. Apply multiple algorithms simultaneously to see which one works the best



4 Introduction to Predictive Analysis II

4.1 Time Series
Learn how to make predictions using time dependent/variant data

4.2 Decision Trees
Tree-based model that is simple and easy to use. Learn the fundamentals on how to implement them

4.3 Support Vector Machines
Learn to classify data points using support vectors

4.4 Neural networks
Master Feed-forward, Recurrent and Gaussian Neural Networks. This is your way into AI

4.5 Association Rule Mining
Ever wondered why beer is kept next to diaper in superstores? Find out in this module






 

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