topic Re: Getting started with data science in Data Science

Getting started with data science

Dokta1017 — Sat, 08 Nov 2025 21:17:15 GMT

What's the best way to get started with data science, preferably for newbies

Re: Getting started with data science

sawaira-iqbal03 — Sun, 09 Nov 2025 15:01:58 GMT

Hi, I am new here How do i start data science? I have some knowledge, but main purpose to do practical work.

Re: Getting started with data science

Anonymous — Mon, 10 Nov 2025 06:31:43 GMT

Hi Dokta1017 ,

Thank you for reaching out to the Microsoft Community Forum.

For getting started, begin with the fundamentals, Python basics, SQL querying, and introductory statistics. Once you are comfortable with these core building blocks, you can start applying them in practical scenarios.

Microsoft Fabric provides an end-to-end environment where you can practice notebook development, Lakehouse data preparation, and visualization with Power BI all in one integrated experience.

The below Microsoft doc provides a guided learning path for beginners to start hands-on with Fabric data science workloads:

Data science in Microsoft Fabric - Microsoft Fabric | Microsoft Learn

Data science tutorial - get started - Microsoft Fabric | Microsoft Learn

This helps you progress step by step from basic concepts to applying them in real projects within a scalable environment. If you have a particular use case in the future, you’re welcome to share it here.

Thank you.

Re: Getting started with data science

Anonymous — Thu, 13 Nov 2025 10:40:47 GMT

Hi Dokta1017 ,

I wanted to follow up on our previous suggestions. We would like to hear back from you to ensure we can assist you further.

Thank you.

Re: Getting started with data science

Anonymous — Tue, 18 Nov 2025 02:04:17 GMT

Hi Dokta1017 ,

We haven’t received an update from you in some time. Could you please let us know if the issue has been resolved?
If you still require support, please let us know, we are happy to assist you.

Thank you.

Re: Getting started with data science

santhoshini9 — Tue, 18 Nov 2025 02:42:16 GMT

Need to goo

Re: Getting started with data science

_dkydv77_ — Sun, 28 Jun 2026 04:07:26 GMT

The best way to start data science as a beginner is to follow a structured roadmap. Focus on practical skills rather than overwhelming yourself with advanced math and theory up front. Master the core pillars of programming, statistics, data manipulation, and machine learning, and practice them on real-world datasets.

Re: Getting started with data science

Drskm143 — Sun, 28 Jun 2026 08:36:21 GMT

Sushanta kumar mohanty

Re: Getting started with data science

Drskm143 — Sun, 28 Jun 2026 08:37:11 GMT

Thank you Microsoft,

Re: Getting started with data science

Drskm143 — Sun, 28 Jun 2026 08:37:13 GMT

Thank you Microsoft,

Re: Getting started with data science

Tarun_khudiya — Mon, 29 Jun 2026 07:03:11 GMT

🔢 1. Learn the Core MathematicsStudy descriptive statistics.Understand probability distributions.Learn basic linear algebra.🐍 2. Master Programming & DatabasesChoose Python as your primary language.Learn SQL to query databases.Practice writing clean code daily.📊 3. Explore Data Analysis ToolsLearn Pandas for data manipulation.Use NumPy for numerical data.Use Matplotlib for visual charts.🤖 4. Understand Machine Learning BasicsStart with linear regression.Learn basic classification algorithms.Practice using the Scikit-Learn library.💼 5. Build Projects & PortfolioDownload free datasets from Kaggle.Clean and analyze messy data.Upload your code to GitHub.

Re: Getting started with data science

Tarun_khudiya — Mon, 29 Jun 2026 07:05:42 GMT

Platform: Microsoft Fabric Community Forum (://microsoft.com).Recipient: A user named Dokta1017.Sender: An anonymous support or community account.Message: The system is checking in because there has been no recent activity on the support thread. They want to know if the problem is fixed or if further technical assistance is required.How to Respond on the ForumIf this is your forum post, you should log into the community site and reply to the thread with one of two options:If resolved: Briefly explain what fixed the problem so it can help other community members facing the same issue.If unresolved: Provide updated details, error logs, or screenshots showing what is still broken so the support team can continue troubleshooting.

Re: Getting started with data science

Tarun_khudiya — Tue, 30 Jun 2026 03:52:58 GMT

1. Learn a Programming LanguagePython: Master basic syntax, loops, and data structures.Libraries: Learn Pandas and NumPy for data manipulation.2. Master Essential Math & StatisticsDescriptive Statistics: Understand mean, median, mode, and standard deviation.Probability: Learn distributions, probability rules, and Bayes' theorem.Linear Algebra: Focus on matrices and vectors.3. Learn Data Querying & VisualizationSQL: Master database queries, joins, and aggregations.Visualization: Learn tools like Power BI, Tableau, or Python libraries like Seaborn.4. Build Projects & PracticeKaggle: Join beginner competitions and explore open datasets.GitHub: Store your code and build a portfolio to showcase your work.

Re: Getting started with data science

Tarun_khudiya — Wed, 01 Jul 2026 04:01:32 GMT

Step 1: Learn Core MathematicsStatistics: Focus on probability, distributions, and hypothesis testing.Linear Algebra: Learn matrices, vectors, and eigenvalues.Calculus: Understand derivatives and gradients for optimization.Step 2: Master Programming & SQLPython: Learn core syntax, loops, functions, and data structures.SQL: Master querying databases, joins, aggregations, and subqueries.Step 3: Learn Data Analysis & VisualizationPandas & NumPy: Master data manipulation and cleaning.Matplotlib & Seaborn: Learn to create charts and plots.EDA: Practice Exploratory Data Analysis to find trends.Step 4: Understand Machine Learning BasicsScikit-Learn: Learn this primary Python library for modeling.Algorithms: Study regression, classification, and clustering techniques.Evaluation: Understand metrics like accuracy, precision, and recall.Step 5: Build Projects & Share PortfolioKaggle: Practice on real-world datasets and entry-level competitions.GitHub: Store your clean code and document your projects.Portfolio: Create 2-3 end-to-end projects showing data cleaning to prediction.