Overview of Analytics Course in Gorakhpur

Gorakhpur, a city situated in the eastern part of the Indian state of Uttar Pradesh, is slowly emerging as an educational hub in the region. With the rise of data science and analytics, there is a growing demand for professionals who can make sense of large datasets, derive insights, and inform business decisions. To meet this demand, several institutions in Gorakhpur now offer analytics courses. Analytics is the process of using data to derive insights and inform decision-making. This is a crucial skill in today's data-driven world, where businesses need to understand their customers, market trends, and competitors to gain a competitive edge. An analytics course can help individuals acquire the skills necessary to excel in this field. The analytics courses in Gorakhpur cover a range of topics, including statistical analysis, data mining, machine learning, and data visualization. These courses are designed to provide both theoretical knowledge and practical skills through hands-on exercises and projects. Students learn how to collect, clean, and analyze data using tools like Python, R, and SQL. One of the institutions offering an analytics course in Gorakhpur is the Indian Institute of Management (IIM) Lucknow - Gorakhpur Campus. IIM Lucknow is a premier management institution in India renowned for its rigorous academic curriculum and experiential learning opportunities. The analytics course at IIM Lucknow is designed to equip students with the skills necessary to be successful in data science and analytics roles across various industries. The course features lectures from industry experts and renowned faculty members, hands-on exercises, and case studies on real-world problems. Students learn how to use statistical methods to analyze data and make informed decisions. They also gain insights into how companies use data to drive business strategy and create value. Another institution offering analytics courses in Gorakhpur is the Gorakhpur Institute of Technology (GIT). GIT is a renowned engineering college that offers various undergraduate and postgraduate courses in engineering and management. The analytics courses at GIT cover topics like data analysis, predictive modeling, and machine learning. Students learn how to use tools like Python, R, and Tableau to build predictive models and create meaningful visualizations. The courses at GIT include several practical projects and real-world applications, allowing students to apply their knowledge in a practical setting. The faculty members are highly qualified and experienced in the field of data science and analytics. In conclusion, an analytics course in Gorakhpur can help individuals acquire the skills necessary to excel in the field of data science and analytics. With the rise of data-driven decision-making across various industries, the demand for professionals with these skills is only going to increase. By enrolling in an analytics course, students can gain a competitive edge and position themselves for a rewarding career in this 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 Gorakhpur?

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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