Overview of Analytics Course in Bhopal

Bhopal, the capital city of Madhya Pradesh, has emerged as a promising education hub over the years, thanks to its high-quality institutions that offer various courses across diverse domains. In recent times, there has been a growing demand for analytics courses in Bhopal, as organizations increasingly seek data-driven insights to make more informed business decisions. Analytics courses in Bhopal are designed to equip students with the necessary quantitative and analytical skills to understand complex data sets, identify patterns and trends, and generate meaningful insights that can inform decision-making. These courses cover a range of topics, including statistics, data mining, machine learning, and data visualization, among others. Given the increasing demand for skilled analytics professionals, these courses offer promising career prospects, both in India and abroad. One of the prominent institutions offering analytics courses in Bhopal is the Indian Institute of Information Technology (IIIT) Bhopal. The institute offers a Master of Technology (MTech) program in Data Science and Analytics, aimed at training students in machine learning, data mining, statistical modeling, and other relevant areas. The program also offers opportunities to work on industry projects, giving students hands-on experience with real-world data analysis challenges. Apart from IIIT Bhopal, other institutions offering analytics courses in Bhopal include the National Institute of Technical Teachers' Training and Research (NITTTR), Bhopal, the Maulana Azad National Institute of Technology (MANIT), and the Rajiv Gandhi Proudyogiki Vishwavidyalaya (RGPV). Apart from institutional training, there are also several analytics training providers in Bhopal that offer short-term courses and workshops aimed at bridging the skills gap in the industry. These courses are typically industry-relevant and focus on practical skills that are in high demand among employers. They cover topics such as Python and R programming, data visualization, and big data analytics tools like Hadoop and Spark, among others. Some of the popular analytics training providers in Bhopal include Analytics Path, Edupristine, and Simplilearn. Overall, an analytics course in Bhopal offers a compelling option for students looking to pursue a career in this rapidly evolving field. With a robust curriculum that covers theoretical concepts and practical know-how, as well as access to cutting-edge tools and technologies, these courses provide a solid foundation for students to explore exciting career opportunities in analytics. Moreover, the growing demand for skilled analytics professionals across industries promises a bright future for those who choose to pursue a 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 Bhopal?

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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