Overview of Analytics Course in Berlin

Berlin is a city known for its vibrant culture, growing economy, and excellent education system. Among the many sought-after courses in Berlin, analytics courses stand out as having the potential to open doors to exciting job prospects and a fulfilling career. Analytics courses can be studied at various levels, ranging from certificate programs to master's degrees. The courses cover topics such as data analysis, data visualization, statistical modeling, predictive modeling, and machine learning techniques. The skills learned in these courses can be applied to various industries, including finance, healthcare, logistics, marketing, and tech, where data is becoming an increasingly important asset. One of the popular universities in Berlin that offer analytics courses is the Humboldt University of Berlin, which has a Master's program in Data Science. This program provides students with knowledge and skills in data analysis and machine learning techniques. The course curriculum includes courses in Mathematics, Programming, Statistics, Data Mining, and Artificial Intelligence. Students also undertake practical projects and internships to gain real-world experience. The Technical University of Berlin provides a Bachelor's and Master's program in Data Engineering, where students learn to extract, process, and analyze large datasets from various sources. The course covers topics such as data storage, data processing, data analysis, and data visualization. Students also gain practical experience through internships and research projects. The Berlin School of Economics and Law also offers Master's courses in Business Analytics, which are designed for professionals looking to enhance their knowledge and skills in data analytics. The program includes courses in statistics, machine learning, data visualization, and data ethics. Students also undertake practical projects and work with real data sets to gain practical experience. In addition to these established universities, there are also private institutions and online training programs in Berlin that offer analytics courses. For instance, the Berlin School of Digital Business provides a six-month program in Data Science and Analytics, where students learn data analysis, data exploration, data visualization, and data modeling. The program can be studied full-time or part-time, and the curriculum includes hands-on projects and industry use cases. Furthermore, the Data Science Society in Berlin offers training programs, workshops, and mentorship programs in data analytics to enhance skills and improve knowledge in analytics. Apart from academic institutions and private organizations, there are also several companies in Berlin that offer job opportunities in data analytics. Some of the popular job titles in this field in Berlin include data analyst, data scientist, machine learning engineer, and business intelligence analyst. In conclusion, pursuing an analytics course in Berlin can open up opportunities for a rewarding career in various sectors. The city provides a rich educational system, a diverse job market, and a growing community of data enthusiasts. Whether studying at a university or a private institution, or pursuing an online program, students can gain practical skills and experience, and meet industry professionals to help them transition into data analysis roles successfully.
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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 Berlin?

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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