𝟱 𝗙𝗿𝗲𝗲 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗬𝗼𝘂 𝗖𝗮𝗻’𝘁 𝗠𝗶𝘀𝘀😍

Microsoft Learn is offering 5 must-do courses for aspiring data scientists, absolutely free🔥📊

These self-paced learning modules are designed by industry experts and cover everything from Python and ML to Microsoft Fabric and Azure🎯

𝐋𝐢𝐧𝐤👇:-

https://pdlink.in/4iSWjaP

Job-ready content that gets you results✅️

How to enter into Data Science

👉Start with the basics: Learn programming languages like Python and R to master data analysis and machine learning techniques. Familiarize yourself with tools such as TensorFlow, sci-kit-learn, and Tableau to build a strong foundation.

👉Choose your target field: From healthcare to finance, marketing, and more, data scientists play a pivotal role in extracting valuable insights from data. You should choose which field you want to become a data scientist in and start learning more about it.

👉Build a portfolio: Start building small projects and add them to your portfolio. This will help you build credibility and showcase your skills.

𝗕𝗼𝗼𝘀𝘁 𝗬𝗼𝘂𝗿 𝗦𝗸𝗶𝗹𝗹𝘀 𝘄𝗶𝘁𝗵 𝗧𝗵𝗲𝘀𝗲 𝗙𝗿𝗲𝗲 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀😍

Ready to take your career to the next level?📊📌

These free certification courses offer a golden opportunity to build expertise in tech, programming, AI, and more—all for free!🔥💻

𝐋𝐢𝐧𝐤👇:-

https://pdlink.in/4gPNbDc

These courses are your stepping stones to success✅️

9 tips to learn programming faster:

Build small projects from day 1

Don’t memorize, understand the logic

Learn by debugging your own code

Google is your best friend

Break big problems into chunks

Teach others what you’ve learned

Be consistent — code daily

Read others' code on GitHub

Don’t rush — master the basics

Free Programming Resources: https://whatsapp.com/channel/0029VahiFZQ4o7qN54LTzB17

ENJOY LEARNING 👍👍

𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗩𝗶𝗿𝘁𝘂𝗮𝗹 𝗜𝗻𝘁𝗲𝗿𝗻𝘀𝗵𝗶𝗽 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝘀 𝗜𝗻 𝗧𝗼𝗽 𝗖𝗼𝗺𝗽𝗮𝗻𝗶𝗲𝘀😍

1️⃣ BCG Data Science & Analytics Virtual Experience
2️⃣ TATA Data Visualization Internship
3️⃣ Accenture Data Analytics Virtual Internship

𝐋𝐢𝐧𝐤👇:-

https://pdlink.in/409RHXN

Enroll for FREE & Get Certified 🎓

Prompt Engineer vs Data Scientist 😅

𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 𝟭𝟬𝟬% 𝗙𝗿𝗲𝗲 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗳𝗼𝗿 𝗔𝘇𝘂𝗿𝗲, 𝗔𝗜, 𝗖𝘆𝗯𝗲𝗿𝘀𝗲𝗰𝘂𝗿𝗶𝘁𝘆 & 𝗠𝗼𝗿𝗲😍

Want to upskill in Azure, AI, Cybersecurity, or App Development—without spending a single rupee?👨‍💻🎯

Enter Microsoft Learn — a 100% free platform that offers expert-led learning paths to help you grow📊📌

𝐋𝐢𝐧𝐤👇:-

https://pdlink.in/4k6lA2b

Enjoy Learning ✅️

Hyperparameter tuning is the process of selecting the optimal set of hyperparameters for a machine learning model to improve its performance. Hyperparameters are parameters that are set before the learning process begins and control the learning process itself, such as the learning rate, number of hidden layers in a neural network, or the depth of a decision tree.

Here is how hyperparameter tuning works:

1. Define Hyperparameters: The first step is to define the hyperparameters that need to be tuned. These are typically specified before training the model and can significantly impact the model's performance.

2. Choose a Search Space: Next, a search space is defined for each hyperparameter, which includes the range of values or options that will be explored during the tuning process. This can be done manually or using automated tools like grid search, random search, or Bayesian optimization.

3. Evaluation Metric: An evaluation metric is selected to measure the performance of the model with different hyperparameter configurations. Common metrics include accuracy, precision, recall, F1 score, or area under the curve (AUC).

4. Hyperparameter Optimization: The hyperparameter tuning process involves training multiple models with different hyperparameter configurations and evaluating their performance using the chosen evaluation metric. This process continues until the best set of hyperparameters that optimize the model's performance is found.

5. Cross-Validation: To ensure the robustness of the hyperparameter tuning process and avoid overfitting, cross-validation is often used. The dataset is split into multiple folds, and each fold is used for training and validation to assess the model's generalization performance.

6. Model Selection: Once the hyperparameter tuning process is complete, the model with the best hyperparameter configuration based on the evaluation metric is selected as the final model.

Hyperparameter tuning is a crucial step in machine learning model development as it can significantly impact the model's accuracy, generalization ability, and overall performance. By systematically exploring different hyperparameter configurations, data scientists can fine-tune their models to achieve optimal results for specific tasks and datasets.

Best Data Science & Machine Learning Resources: https://topmate.io/coding/914624

Credits: https://news.1rj.ru/str/datasciencefun

Like if you need similar content 😄👍

Hope this helps you 😊

𝗟𝗲𝗮𝗿𝗻 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗳𝗿𝗼𝗺 𝗚𝗼𝗼𝗴𝗹𝗲 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝘀 — 𝗙𝗼𝗿 𝗙𝗿𝗲𝗲!😍

Want to break into machine learning but not sure where to start?💻

Google’s Machine Learning Crash Course is the perfect launchpad—absolutely free, beginner-friendly, and created by the engineers behind the tools.👨‍💻📌

𝐋𝐢𝐧𝐤👇:-

https://pdlink.in/4jEiJOe

All The Best 🎊

𝗙𝗥𝗘𝗘 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 😍

Feeling like your resume could use a boost? 🚀

Let’s make that happen with Microsoft Azure certifications that are not only perfect for beginners but also completely free!🔥💯

𝐋𝐢𝐧𝐤👇:-

https://pdlink.in/4iVRmiQ

Essential skills for today’s tech-driven world✅️

Steps to become data analyst when you are fresher 👇👇

1 - First try to focus 3 mandatory skills i.e. Sql, Ms excel and python -

- For sql you can refer Ankit Bansal Or Thoufiq Mohammed (techtfq) on @sqlanalyst
- For Ms excel refer Leila Gharani or @excel_analyst
- For python refer freecodecamp from YouTube or @pythonanalyst

2 - After that try to be clear with basic idea of tableau or powerbi. (Not mandatory for every job). You can refer this channel for free resources https://news.1rj.ru/str/PowerBI_analyst

3 - Add your college project in your resume, if it's a data science related project it will help a lot. If you don't have project then you can make some dashboarding projects from YouTube in tableau/powerbi.

4 - And start applying for jobs which is having 0-1 yr experience required, you can also apply for 1 yr experience required job in analytics because sometimes they may consider fresher also. You can refer this channel @jobs_sql for job opportunities