Data Science
Share
It's all about data science and related to statistics.
25/11/2025
Collected
19/11/2025
Machine learning cheatsheet
13/11/2025
Traditional ML vs Modern ML — Easy Comparison for Data Science Learners
If you're studying Data Science or preparing for jobs, this chart will help you understand what has changed in machine learning.
🔵 Traditional Machine Learning (Old Era)
Used in statistics, econometrics & small datasets.
✔ Linear / Logistic Regression
✔ SVM, KNN
✔ Decision Trees, Random Forest
✔ XGBoost
📌 Best for: tabular data, small datasets, scoring models
📌 Needs: manual feature engineering
📌 Easy to interpret (coefficients, trees)
📌 Trains fast on a laptop
🟢 Modern ML / AI Models
Used in NLP, images, video, multimodal tasks.
🔥 GPT-5.1, Claude 3.5, Gemini 2.0
🔥 Stable Diffusion 3, Sora
🔥 Graph Neural Networks
🔥 Time-series Foundation Models (Chronos, Moirai)
🔥 Tabular Transformers
📌 Best for: text, image, time-series, graphs, multimodal
📌 Learns features automatically
📌 Zero-shot, few-shot capability
📌 Pretrained on massive data (billions!)
⭐ Core Differences:
Traditional ML Modern ML
Needs small datasets Learns from huge datasets
Manual feature engineering Automatic feature learning
High interpretability Harder to interpret
Good for structured data Best for unstructured & multimodal
Trains locally Mostly API / cloud models
Single-task Multi-task generalization
06/11/2025
Matrix
03/11/2025
Hahaha, it’s true 😂
Core Goals of Data Science
1. Understanding Data
• Collect, clean, and organize raw data from different sources.
• Explore patterns, trends, and anomalies.
2. Knowledge Discovery
• Use statistical methods and machine learning to uncover relationships.
• Turn complex data into understandable insights.
3. Prediction & Forecasting
• Build models (e.g., regression, classification, time series) to predict future outcomes.
• Example: Predict fuel prices, customer demand, or disease risk.
4. Decision Support
• Provide evidence-based recommendations.
• Help businesses, governments, or researchers make smarter choices.
5. Automation
• Develop algorithms that can make real-time decisions without human intervention.
• Example: Spam filters, fraud detection, recommendation systems.
6. Optimization
• Find the most efficient or cost-effective solution.
• Example: Route optimization, resource allocation, policy design.
Master's courses second part of Data Science University lists:
8.
University Name: Hamburg University of Technology
Subject name: Data Science
IELTS: 6.5
Application process: Directly at the University
Type: Non-restricted Course
Application last Date:
Summer 15 Jan
Winter 15 Jul
9.
University Name: University of Hildesheim
Subject name: Data Analytics
IELTS: 6
Additional document: Medium of Instruction Certificate (MOI)
Application process: Directly at the University
Type: Restricted Course
Application last Date:
Winter 30 Jun
10.
University Name: University of Applied Sciences Mittweida
Subject name: Network & Data Science
IELTS: 6
Application process: Directly at the University
Type: Non-restricted Course
Application last Date:
Winter 15 July
11.
University Name: Berliner Hochschule für Technik (BHT)
Subject name: Data Science
IELTS: B2 (not mentioned exact score)
Application process: Uni-Assist
Type: Local Restricted Course
Application last Date:
Winter 15 June
12.
University Name: Bielefeld University
Subject name: Data Science
IELTS: B2
Application process: Directly at the University (Including fees)
Type: Restricted Course
Application last Date:
Winter 15 Jul
13.
University Name: University of Cologne
Subject name: Business Analytics & Econometrics
IELTS: B2
Required: VPD from Uni-assist
Application process: Directly at the University
Type: Restricted Course
Application last Date:
Winter 15 Jun
14.
University Name: RWTH Aachen University
Subject name: Data Science
IELTS: 5.5
Additional document: Medium of Instruction Certificate (MOI)
Application process: Directly at the University
Type: Non-restricted Course
Application last Date:
Winter 1 Mar &
Summer 1 Sep
RWTH Aachen University is the largest university of technology in Germany and one of the most renowned in Europe.
15.
University Name: Freie Universität Berlin
Subject name: Data Science
IELTS: 6
Application process: Uni-assist
Type: Restricted Course
Application last Date:
Winter 31 May
You can check the updated information through these websites:
*Mygermanuniversity
*DAAD International
*University website
*Masterportal
Some more University list will be post soon. Keep eyes open, on this page.
Good luck 🖤
Data Scientist Roadmap
1. Mathematics & Statistics: Develop a solid understanding of probability theory, hypothesis testing, linear algebra (vectors, matrices), inferential statistics, descriptive statistics, and calculus. These concepts are fundamental for data analysis and machine learning algorithms.
2. Python: Gain proficiency in Python, including functions, data types, control structures, Pandas, Numpy, Scikit-Learn, syntax, data visualization, Matplotlib, Plotly, TensorFlow, PyTorch, data analysis, and Seaborn. Python is the backbone of data science programming.
3. SQL: Master SQL basics such as SELECT, INSERT, UPDATE, DELETE, as well as joins, subqueries, window functions, data optimization, database management, query optimization, and stored procedures. These skills are essential for working with large datasets.
4. Data Wrangling: Learn to handle missing values, data transformation, data normalization, and data cleaning efficiently. These tasks are key in preparing data for analysis.
5. Data Visualization: Use tools like Bokey, Plotly, Seaborn, Taipy, Matplotlib, PowerBI, Looker, and Tableau to create compelling visualizations that communicate insights effectively.
6. Machine Learning: Dive into supervised learning, unsupervised learning, linear regression, logistic regression, decision trees, K-means clustering, hierarchical clustering, model evaluation, cross-validation, and ROC curve. Mastering these techniques is critical for building robust models.
7. Soft Skills: Enhance your problem-solving skills, critical thinking, communication skills, collaboration and teamwork, storytelling with data, presentation skills, and adaptability. These soft skills are vital for collaborating with teams and stakeholders effectively.
Collect from Denis Panjuta
Masters in Data Science at the German University lists:
1.
University Name: Kiel University of Applied Sciences
Subject name: Data Science
IELTS: 5.5 - 6.5
GRE required
Addition: Medium of Instruction (MOI)
Application process: Uni-assist
Type: Non-Restricted Course
Application last Date:
Summer November until 15.03
Winter May until 15.09
2.
University Name: Technische Universität Braunschweig
Subject name: Data Science
IELTS: 6 - 6.5
Application process: Directly at the University
Type: Restricted Course
Application last Date:
Summer 15 September
Winter 15 March
3.
University Name: University of Potsdam
Subject name: Data Science
IELTS: 7
Addition: Medium of Instruction (MOI)
Application process: Uni-assist (free apply)
Type: Restricted Course
Application last Date:
Winter 1 June
4.
University Name: Trier University
Subject name: Data Science
IELTS: 6.5
Application process: Directly at the University (including a 70 euro bank transfer)
Type: Restricted Course
Application last Date:
Winter 31 May
5.
University Name: TU Bergakademie Freiberg
Subject name: Data and Resource Sciences
IELTS: 6.5
Application process: Directly at the University
Type: Restricted Course
Application last Date:
Winter 15 April
6.
University Name: Leuphana University Lüneburg
Subject name: Management & Data Science
IELTS: 5.5
Application process: Uni-assist
Type: Restricted Course
Application last Date:
Winter 1 May
7.
University Name: Friedrich Schiller University Jena
Subject name: Business Mathematics
IELTS: 5.5
Interviews will be taken
Application process: Directly at the University
Type: Restricted Course
Application last Date:
Summer: Summer 15 Jan
Winter: Winter 15 Jul
It will be continued....
Click here to claim your Sponsored Listing.
Category
Website
Address
Rangpur
5400