Overview of Analytics Course in Ghaziabad

Analytics is the process of collecting, analyzing, and interpreting data to gain insights and make informed decisions. With the rise of big data and technology, organizations have realized the importance of data analytics to drive growth and profitability. As a result, there is a growing demand for skilled analytics professionals, and this has led to the emergence of analytics courses in various parts of India, including Ghaziabad. Ghaziabad is a leading industrial city in Uttar Pradesh, and it has a well-established education system. There are several institutes offering analytics courses in Ghaziabad, catering to the growing demand for skilled professionals in the field. Many of these analytics courses in Ghaziabad are designed to provide students with a solid foundation in statistical analysis, data modeling, and predictive analytics. The courses also cover topics such as data visualization, machine learning, and artificial intelligence, which are becoming increasingly important in the world of analytics. One of the popular courses in Ghaziabad is the Post Graduate Diploma in Data Science and Analytics offered by the Institute of Management Technology (IMT). This program is designed for graduates from any discipline and covers essential concepts in data science, including statistics, data mining, and machine learning. It also provides hands-on experience with popular analytics tools and frameworks, such as Python, R, and Hadoop. Another noteworthy course is the Executive Program in Business Analytics offered by the Institute of Management Studies (IMS). This course is designed for working professionals who want to upskill and gain expertise in analytics. The program covers topics such as data analysis, statistical modeling, and data visualization. It also includes case studies and projects that enable participants to apply their knowledge to real-world problems. Apart from these institutes, there are several other analytics courses in Ghaziabad that offer similar curriculum and training. However, it is essential to choose a course that fits your aspirations and career goals. You should consider factors such as course duration, fee structure, and placement opportunities before selecting a program. Analytics is a growing field, and there is a high demand for skilled professionals. According to a report by NASSCOM, India is expected to need 2.4 lakh data professionals by 2020, and this number will increase in the future. Therefore, pursuing an analytics course in Ghaziabad can provide you with the skills and knowledge to build a successful career in this field. In conclusion, analytics is a critical field that is essential to the success of modern organizations. Analytics courses in Ghaziabad offer an excellent opportunity for students and working professionals to acquire the necessary skills and knowledge to excel in this field. With its well-established education system and growing industrial sector, Ghaziabad is an ideal destination for those who want to pursue a career in analytics.
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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 Ghaziabad?

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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