Overview of Analytics Course in Warangal

Warangal has emerged as a hub for education, and the city's educational institutions offer a diverse range of courses to local and international students. Among these courses, analytics has recently gained popularity due to its growing demand in various industries. Analytics has become an essential factor in decision-making processes for businesses across all sectors. With the huge amount of data being generated every day, it has become all the more necessary to employ professionals who can analyze this data and make sense of it. This is where analytics comes in. Several educational institutions in Warangal now offer courses in analytics to cater to the growing demand for skilled analytics professionals. One such institution is the National Institute of Technology Warangal (NITW), which offers a two-year master's program in analytics in collaboration with Purdue University in the United States. The program provides students with theoretical knowledge and hands-on experience in data analytics, machine learning, and big data. The program's curriculum has been designed to equip students with the skills needed to solve real-world problems through data analysis. Another institution that offers an analytics course in Warangal is the SR Engineering College. The college offers a three-month certificate course in data analytics, which covers topics such as data visualization, predictive modeling, and data mining. The course is designed for working professionals who want to upskill or for students who want to pursue a career in analytics. In addition to these, the Kakatiya Institute of Technology and Science (KITS) also offers a two-year master's program in data analytics. The program is designed to provide students with a strong foundation in data analytics and statistics. The curriculum includes courses in data structures, algorithms, statistical modeling, and data visualization. Students who take an analytics course in Warangal can expect to gain a range of skills. These include proficiency in programming languages like R and Python, knowledge of statistical techniques, and an in-depth understanding of machine learning algorithms. Graduates of analytics courses in Warangal can expect to find employment opportunities in various fields such as healthcare, finance, marketing, and e-commerce. Analytics professionals in Warangal can expect to earn competitive salaries. According to Glassdoor, the average salary for a data analyst in India is INR 6.5 lakhs per annum, with salaries ranging from INR 3 lakhs to INR 15 lakhs per annum. In conclusion, the analytics courses offered in Warangal provide students with valuable skills in data analysis, machine learning, and statistical modeling. These courses are designed to prepare students for the demands of the modern workplace and provide them with the tools and techniques needed to solve complex problems through data analysis. With Warangal's growing status as an education hub, students can expect a quality education and promising career opportunities in the analytics field.
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Skill Level

NA

Internship

NA

Live Project

NA

Certificate

NA

Live Training

NA

Career Assistance

NA

Expiry Period

Lifetime
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Skillfloor Course Training Process
Skillfloor Course Training Process

Internship Certificate

internship certificate

Completing this Analytics Course certifies your proficiency in data analysis, statistical methods, and essential analytics tools. This certification shows you can transform raw data into actionable insights, improving decision-making in various business contexts. It indicates your understanding of data visualization, predictive modelling, and data-driven strategy development, providing you with the skills to excel in analytics. This credential reflects your dedication to continuous learning and commitment to leveraging data for strategic advantage.

Analytics Tools Covered

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Why Choose SKILLFLOOR for Analytics in Warangal?

Why Course Training in Skillfloor

Syllabus

- Overview of data analysis and its importance in business

- Types of analytics: Descriptive, Predictive, Prescriptive

- Role of data in decision-making processes

- Introduction to common tools: Tableau, PowerBI, Excel

- Ethical considerations in data collection and analysis

- Data sources: Primary and secondary data

- Data collection methods (surveys, web scraping, databases)

- Data cleaning techniques (handling missing values, outliers)

- Data transformation and feature engineering

- Data storage concepts (structured vs. unstructured data)

- Descriptive statistics: Mean, median, mode

- Data visualization basics (histograms, scatter plots)

- Identifying data patterns and trends

- Outlier detection and handling methods

- Correlation and causation analysis

- Inferential statistics and probability theory

- Hypothesis testing (t-tests, chi-square tests, ANOVA)

- Measures of central tendency and variability

- Confidence intervals and margin of error

- Regression analysis: Linear and logistic regression

- Principles of effective data visualization

- Types of charts and their uses (bar, line, pie, heatmaps)

- Designing dashboards for different audiences

- Interactive visualization techniques

- Data storytelling for impactful presentations

- Time series analysis and forecasting methods

- Clustering and segmentation analysis

- Decision trees and classification techniques

- Introduction to machine learning in business analytics

- Model evaluation and selection

- Basics of SQL for data manipulation

- Creating databases and relationships

- Aggregating data with SQL (GROUP BY, JOIN)

- Data modeling for business intelligence (star and snowflake schemas)

- Case study: Building a business model with SQL

- Connecting and preparing data in Tableau

- Creating basic visualizations (charts, maps)

- Advanced Tableau functions (LOD calculations, table calculations)

- Building interactive dashboards and stories

- Publishing and sharing visualizations on Tableau Server/Online

- Introduction to PowerBI workspace and components

- Data import and transformation with Power Query

- Data modeling and relationships in PowerBI

- Creating and customizing visualizations

- Publishing and collaborating on PowerBI Service

- Selecting a real-world dataset for analysis

- Defining business questions and objectives

- Conducting data analysis and visualization

- Presenting findings in a comprehensive dashboard

- Peer review and feedback on project

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