Overview of Analytics Course in Kochi

The world is rapidly moving towards data-driven decision making, and organizations of all sizes are now realizing the value of incorporating analytics in their operations. Abu Dhabi, being a global business hub, is no exception, and is witnessing a growing demand for analytics experts. As a result, many educational institutions in Abu Dhabi have launched analytics courses to fulfill this demand. Analytics courses in Abu Dhabi focus on providing students with the knowledge and skills needed to analyze, visualize, and manipulate data, and utilize it to drive business decisions. These courses typically cover various topics such as data mining, statistical analysis, predictive analytics, machine learning, and data visualization. Moreover, analytics courses at Abu Dhabi institutions are designed to cater to both beginners and seasoned professionals, offering a blend of theoretical and practical knowledge. One of the key benefits of studying analytics in Abu Dhabi is the opportunity to learn from experienced professionals actively working in the industry. Many courses offer hands-on training and real-world case studies, providing students with practical experience in the field. Moreover, students can network with professionals in various industries and gain insights into the latest analytics trends and developments. Abu Dhabi offers students a wide range of analytics courses across various levels, from short-term courses to full-time postgraduate programs. Some universities and educational institutions even offer customized programs tailored to meet specific organizational needs, allowing students to learn about analytical techniques and tools that are specific to their industry. The cost of analytics courses in Abu Dhabi varies depending on the duration, level of the program, and the institution offering it. However, many institutions offer scholarships and financial aid packages to support students who need financial assistance. In addition to academic programs, Abu Dhabi hosts several analytics-related events, workshops, and conferences that provide students with opportunities to learn from industry experts and network with industry professionals. These events cover current trends, issues, and challenges in the field of analytics. In conclusion, analytics courses in Abu Dhabi offer students the opportunity to learn about the latest analytical tools and techniques, gain exposure to real-world case studies, and network with professionals in the industry. These courses are designed to cater to both beginners and seasoned professionals, offering flexible, customized, and practical programs. As data-driven decision making becomes increasingly important in business, analytics skills are in high demand, making Abu Dhabi an excellent place to acquire these skills and launch a career in the field of analytics.

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₹70

₹9

Skill Level

Intermediate

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 Kochi?

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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