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31 - DAB- Data Analytics & Business Intelligience
DAB 405 - Business Intelligence and Data Mining (BI & DM)
| Code | Start Date | Duration | Venue | |
|---|---|---|---|---|
| DAB 405 | 21 October 2024 | 5 Days | Istanbul | Registration Form Link |
| DAB 405 | 30 December 2024 | 5 Days | Istanbul | Registration Form Link |
Course Description
Business intelligence (BI) is the ability of an organization to collect, maintain, and organize data. This produces large amounts of information that can help develop new opportunities. Identifying these opportunities, and implementing an effective strategy, can provide a competitive market advantage and long-term stability. The goal of modern business intelligence deployments is to support better business decision-making. Thus a BI system can be called a decision support system (DSS). In this course, participants will first, be learning how do we turn that data into information, knowledge, and extract patterns. Second, they will learn the process of using Python libraries to explore techniques, and approaches which includes data mining, data science, AI, ML, DL, data visualization that identify the sources of data, discern patterns, associations, clusters, and relationships in the data to turn data into meaningful information.
Course Objectives
- Gain the knowledge and confidence to frame the right questions to exploit your data
- Become familiar with how you and your team can extract value from data using advanced analytics over traditional methods
- Gain hands-on experience in applying advanced data science models to make confident, evidence-based decisions and elevate your capacity to provide solutions
- Use cutting-edge methods to identify trends, explore hypotheses, challenge assumptions, and create a more nuanced data-driven understanding of your business
- Master the use of Python libraries to get the job done
Who Should Attend?
- Managers
- Executives
- Data Scientists
- Data Analysts
- Business Analysts
- professionals working with data analytics or business intelligence
- Anyone who needs to understand how to use data to make better decisions.
Course Details/Schedule
Day 1
- Data mining theory & methodology
- Translating business problems into data mining problems
- BI & DM overview
- Model prediction & assessment
- BI case studies
- Using Python as the main tool
- Lab: Introduction with Python to Data Mining
Day 2
- Data exploration and pattern discovery
- Developing intuition about data
- Market basket analysis & association rules
- Clustering and segmentation
- Case study on pattern recognition
- Lab 2: Association Mining and Link Graph by Python
Day 3
- Predictive Modeling (1)
- Classification and predictive modeling
- Decision trees as classification tools
- Using Python to build decision trees
- Lab 3: Predictive Modeling (Decision Trees, Model Comparison )
Day 4
- Predictive Modeling (2):
- Regression Models (Linear & Logistic)
- Using Python to build regression models
- Lab 4: Predictive Modeling (Regression, Variable Selection, Missing Value, Transforming Variable)
Day 5
- Comprehensive assessment of the entire information
- Real-life scenario Project implementation from scratch to completion
