Overview of Analytics Course in Pondicherry
Hands-On Learning: Practical exercises and projects with real-world data are essential to the program. This approach helps students apply their knowledge, solve problems, and gain confidence in their abilities.
Networking Opportunities: Students are encouraged to connect with peers and industry professionals, opening doors to job opportunities and collaborations. SkillFloor also organizes events where students and alumni can meet business leaders.
Expert Trainers: Experienced professionals from the analytics field lead the courses, offering real-world insights and practical tips that help students understand how analytics is used across industries.
Comprehensive Curriculum: The course covers key areas such as data analysis, visualization, and predictive modeling. It combines theoretical concepts with practical skills to prepare students for tackling business challenges.
Focus on Popular Tools: The program teaches students to use powerful tools like Tableau, Power BI, and Excel, which are widely used in analytics jobs, making them highly employable.
Flexible Learning Options: SkillFloor offers both online and classroom sessions, allowing students to choose the mode that fits their schedule and learning style.
Real-World Focus: The course emphasizes using analytics in business scenarios. Students learn to analyze data to make decisions and improve results, equipping them with job-ready skills.
Career Support: Students receive guidance on writing resumes and preparing for interviews, which boosts their confidence and increases their chances of securing a job in analytics.
Final Projects: The program includes projects that allow students to showcase their ability to solve real-world problems. These projects also help build a professional portfolio to impress potential employers.
The Business Analytics Certification in Pondicherry is designed to help participants develop key skills in data analysis and business intelligence. The program covers essential topics such as data visualization, statistical analysis, and the use of popular tools like Tableau and Power BI. Participants will learn how to analyze data effectively and make informed decisions based on their insights. The course includes practical training and hands-on projects, allowing students to apply what they’ve learned in real-world scenarios. Upon completion, participants will receive a certification that demonstrates their expertise in analytics, giving them a competitive edge in the job market.
- 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
