Overview of Analytics Course in Cochin

Analytics is a rapidly growing field that is changing the way businesses operate. With the increasing amount of data being generated every day, the demand for professionals who can analyze and interpret this data is also on the rise. Cochin, a fast-growing city in Kerala, India, has recognized the importance of analytics and has established several institutions that provide courses in this field. One such institute that offers courses in analytics is the Indian Institute of Management Kozhikode (IIMK) Kochi Campus. This campus was set up in 2012 to bring world-class management education to the region. It offers a range of post-graduate programs, including the Executive Post Graduate Program in Analytics (EPGA) for working professionals. The EPGA program is a one-year, part-time program that aims to equip professionals with the skills and knowledge required to become experts in analytics. The program consists of six modules, covering topics such as data analysis, statistical modeling, machine learning, and big data. It also includes a capstone project that allows students to apply their learnings to a real-world problem. Another institution that offers courses in analytics in Cochin is the International School of Engineering (INSOFE). INSOFE is a globally recognized institution that provides post-graduate programs in data science and analytics. The institute has tie-ups with several top-tier universities around the world and offers courses that are at par with international standards. INSOFE offers two post-graduate programs in analytics – the Post Graduate Program in Data Science (PGPDS) and the Post Graduate Program in Business Analytics (PGPBA). Both programs are full-time and last for six months. The PGPDS program focuses on data science fundamentals, while the PGPBA program covers topics related to business analytics such as data visualization, data modeling, and predictive analytics. Another institution that offers courses in analytics in Cochin is the Great Learning Academy. This academy provides online courses in analytics that are designed for working professionals. The courses are taught by experts from the industry and cover topics such as data analytics, machine learning, and artificial intelligence. The academy also offers career support to its students, including resume building, interview preparation, and job placement assistance. In conclusion, the field of analytics is a rapidly growing field that offers tremendous career opportunities. Cochin has recognized the importance of analytics education and has established several institutions that provide courses in this field. These institutions offer a range of programs, from part-time courses for working professionals to full-time post-graduate programs. Whether you are a fresh graduate or a working professional, there is a course in analytics that can help you acquire the skills and knowledge required to succeed in this field.

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₹70

₹9

Skill Level

Beginner

Internship

Yes

Live Project

2

Certificate

Yes

Live Training

Yes

Career Assistance

Yes

Expiry Period

1 Months
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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 Cochin?

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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