TDWI Predictive Analytics Fundamentals (NEW), Germany

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This course introduces the building blocks needed to implement predictive capabilities within an organization. It also helps develop the necessary understanding about how models, people, and decision processes must interact to drive actual business impact. Techniques based on statistics, probability, linear regression, logistic regression, and decision trees are described as key enablers for creating predictive models. Additional topics related to problem framing, data profiling, data preparation, model evaluation, human factors, leadership, and organizational culture are presented as additional and necessary ingredients for success.

There are no prerequisites for this course.

BI and analytics executives, program managers, architects, and project managers
Data-driven business professionals who want to learn how to implement the “power to predict”
Technology professionals who want to develop their understanding of predictive analytics
Business analysts who want to use predictive techniques in their analytics studies
Business managers who want to develop a proactive and predictive decision-making style in their operations
Anyone interested in learning the basics of predictive analytics and how it can drive business improvement

Definitions, concepts, and terminology of predictive analytics
What data science is and how it relates to predictive analytics and BI programs
Purpose, structure, and categories of models
Methods adapted from statistics, data mining, and machine learning
Functionality of predictive models and related development approaches
Common applications and use cases for predictive analytics
How successful predictive capabilities are enabled by human and organizational factors
Essential team composition, skills development, and organization models including roles, responsibilities, and accountabilities
Why business, technical, and management skills are essential for success
Practical guidance for getting started with predictive analytics

Module 1 - Predictive Analytics Concepts

What and Why of Predictive Analytics
- Predictive Analytics Defined
- Business Value of Predictive Analytics
The Foundation for Predictive Analytics
- Statistical Foundation
- Data Mining Foundation
- Machine Learning Foundation
- Data Science Foundation
- Describing Data Science
- The Changing Landscape of Data Sources
Predictive Analytics in BI Programs
- Predictive Analytics in the BI Stack
- Predictive Analytics in the BI Roadmap
- Business, Technical, and Data Dependencies
Becoming Analytics Driven
- Business Driven
- Grass Roots Driven
Common Applications for Predictive Analytics
- What Business Needs to Predict
The Language of Predictive Analytics
- Making Sense of the Terminology

Module 2 - Understanding Models

Overview and Context
- What Are Models?
- How Models Are Used
- Categories of Models
- How Are They Built?
Enabling Techniques
- Contributing Communities
Descriptive Statistics
- Frequencies and Summaries
- Variables
- Relationships
- Dependent and Independent Variables
Understanding Probability
- Statistics Revisited
- Probability
- Probability Examples
- Probability Estimation
- Odds
- Logit Transformation
- Logit Transformation Example
- Probability Distributions
- Symmetrical Continuous Distribution
- Skewed Continuous Distributions
- Discrete Distributions
- Distribution Examples

Module 3 - Regression Model Examples

Regression Models
- Description
Linear Regression Models
- Overview
- Example
- Model Description
Logistic Regression Models
- Overview
- Example
- Steps for Creating the Model
- Model Description
- Model Results
- Predictors and Classifiers
- Predictor and Classifier Example

Module 4 - Building Predictive Models

Model Building Processes
- Data Mining Projects
- CRISP-DM
- SEMMA
- CRISP-DM and SEMMA Compared
Implementation and Operations Teams
- A Team Effort
- Roles and Responsibilities
Predictive Techniques
- Probability Values
- Classification and Clustering
- Segmentation
- Association
- Sequencing
- Forecasting
Technology
- Features and Functions Overview
- The Tools Landscape
Model Building Algorithms
- What and Why
- Some Examples

Module 5 - Implementing Predictive Capabilities

Introductory Concepts
- Distribution View
- Model Types View
- Process View
- Process Overview
Business Understanding
- Activities and Deliverables
- Pragmatics
Data Understanding
- Activities and Deliverables
- Pragmatics
Data Preparation
- Activities and Deliverables
- Pragmatics
Modeling
- Activities and Deliverables
- Pragmatics
Evaluation
- Activities and Deliverables
- Pragmatics
Deployment
- Activities and Deliverables
- Pragmatics

Module 6 - Human Factors in Predictive Analytics

Analytics Culture
- Executive Buy-In
- Strategic Positioning
- Enterprise Range and Reach
- Decision Processes
People and Predictive Analytics
- The Team
- The Range of People
- The Range of Knowledge
- Readiness
- Trust and Motivation
- Expectations and Intent
- Getting from Analytics to Impact
Ethics and Predictive Analytics
- Why Ethics Matters
- Data and Ethics

Module 7 - Getting Started with Predictive Analytics

Predictive Analytics Readiness
- Readiness Checklist
- Executive Commitment
- Organizational Buy-In
- Data Assets
- Human Assets
- Technology Assets
Predictive Analytics Roadmap
- A Plan to Evolve
- An Evolving Plan

TDWI Predictive Analytics Fundamentals (NEW) Training Course in Germany

The Federal Republic of Germany is the second most populous country in Europe and is located in Central Europe. The official language of the country is German. Germany is one of the richest countries in the world. The main exports of the country include motor vehicles and iron and steel products.

Here are some fun facts about Germany:
The fairy tale writer, the Brothers Grimm, came from Germany and wrote many famous stories such as Cinderella, Snow White, and Sleeping Beauty.
Germany is home to the largest theme park in Europe, the Europa-Park.
The famous composer Ludwig van Beethoven was born in Germany.
The Autobahn, the German highway system, is known for having no general speed limit.

Berlin was divided by the Berlin Wall from 1961 to 1989. Known for its street art, Berlin has many colorful murals and graffiti throughout the city. Also, Berlin is home to many famous museums, such as the Pergamon Museum and the Museum Island. Many clubs and bars stay open until the early hours of the morning in this big city.

Another popular city is Munich, which is famous for its Oktoberfest beer festival that attracts millions of visitors every year. Munich is also home to many historic buildings, including Nymphenburg Palace and the Marienplatz town square.

The country's capital and largest city is Berlin, however Frankfurt is considered to be the business and financial center of Germany. It is home to the Frankfurt Stock Exchange, the European Central Bank, and many other financial institutions. Because of its central location within Europe and its status as a major financial hub, Frankfurt is often referred to as the "Mainhattan," a play on the city's name and its association with the Manhattan financial district in New York City.

Frankfurt is also a major transportation hub, with the largest airport in Germany and one of the largest in Europe, Frankfurt Airport. Additionally, it is a popular destination for tourists, with its historic city center, beautiful parks, and vibrant cultural scene.

Some of the top German technology companies like Siemens AG, Bosch, SAP SE, Deutsche Telekom, Daimler AG and Volkswagen has business centers in Frankfurt. The country has a strong tradition of engineering and innovation, and is home to many other world-class technology companies and research institutions.

Tailored to meet the specific needs of Germany, Bilginç IT Academy combines cutting-edge training methodologies with our comprehensive range of Certification Exam preparation courses and accredited corporate training programs. Experience a transformative approach to IT training that will redefine your expectations.

TDWI Predictive Analytics Fundamentals (NEW) Training in Germany

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TDWI Predictive Analytics Fundamentals (NEW) Training in Germany

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