Overview of Analytics Course in Madurai

Madurai, also known as the "Temple City" of India, is a major cultural and commercial hub in Tamil Nadu. With the advent of digitalization, analytics has become a critical component of business decision-making, making this city an attractive destination for those seeking to pursue a career in this field. A number of institutions in Madurai offer analytics courses, providing individuals with an opportunity to gain valuable skills and knowledge in a rapidly growing industry. Analytics is the process of examining data sets to extract insights, trends, and patterns to aid in decision-making. With the increasing amounts of data generated by businesses, analytics has become essential for making effective decisions and staying ahead of competition. Analytics courses in Madurai provide individuals with a range of skills, including statistical and quantitative techniques, data visualization, machine learning, and coding. One popular analytics course in Madurai is the Post Graduate Diploma in Management (PGDM) in Business Analytics offered by the Thiagarajar School of Management (TSM). This course is designed to provide students with a comprehensive understanding of the business ecosystem and the use of analytics to make informed decisions. The course is a combination of classroom learning, case studies, industry visits, and live projects, providing students with hands-on experience and exposure to real-world challenges. Another course is the Data Science program offered by Jigsaw Academy. This course provides students with a strong foundation in data science and analytics, covering topics such as data exploration, data visualization, machine learning, and big data. The course is designed to be flexible, with online and classroom options available, and can be completed in as little as six months. The Indian Institute of Technology (IIT) Madras also offers a Business Analytics program, providing students with an understanding of business analytics and its applications in various industries. The course covers techniques such as data visualization, predictive analytics, and machine learning and is taught by faculty members with extensive industry experience. There are also several online analytics courses offered by platforms such as Coursera and edX, providing flexibility and affordability for those interested in learning at their own pace. These courses offer a range of topics, from basic statistical concepts to advanced machine learning techniques, and are taught by leading experts in the field. In conclusion, analytics courses in Madurai offer individuals the opportunity to gain valuable skills and knowledge in a rapidly growing industry. With a range of options available, from classroom-based courses to online programs, individuals can choose the best fit for their schedule and learning style. Pursuing an analytics course can open up a world of opportunities, providing individuals with the skills to make informed decisions and stay competitive in today's business environment.
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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 Madurai?

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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