Ashley Global Capability Center
Ashley GCC is currently seeking Business Intelligence professionals with 3-10 years of experience. If you are skilled in SQL, Power BI, Tableau, Excel, Python, Azure Synapse, Databricks, and Spark, If you feel you have the necessary skill sets and are passionate about the job, please send your profile to
vthulasiram@ashleyfurnitureindia.com.
The job location is Chennai.

Deloitte is hiring!
Position: Associate Analyst/ Analyst
Qualification: Bachelor’s/ Master’s Degree
Salary: 5 - 8.6 LPA (Expected)
Experience: 0 - 2 (Years)
Location: Hyderabad, India (Work From Home/ Office)

📌Apply Now: https://usijobs.deloitte.com/careersUSI/JobDetail/USI-EH25-Global-CoRe-KS-KX-Assets-Spanish-Analyst/192347

https://usijobs.deloitte.com/careersUSI/JobDetail/USI-EH-FY25-EA-MF-CA-CBS-Admin-Shared-Services-Analyst-Associate-Analyst/191991


Like for more ❤️

All the best 👍👍

How to master Python from scratch🚀

1. Setup and Basics 🏁
- Install Python 🖥️: Download Python and set it up.
- Hello, World! 🌍: Write your first Hello World program.

2. Basic Syntax 📜
- Variables and Data Types 📊: Learn about strings, integers, floats, and booleans.
- Control Structures 🔄: Understand if-else statements, for loops, and while loops.
- Functions 🛠️: Write reusable blocks of code.

3. Data Structures 📂
- Lists 📋: Manage collections of items.
- Dictionaries 📖: Store key-value pairs.
- Tuples 📦: Work with immutable sequences.
- Sets 🔢: Handle collections of unique items.

4. Modules and Packages 📦
- Standard Library 📚: Explore built-in modules.
- Third-Party Packages 🌐: Install and use packages with pip.

5. File Handling 📁
- Read and Write Files 📝
- CSV and JSON 📑

6. Object-Oriented Programming 🧩
- Classes and Objects 🏛️
- Inheritance and Polymorphism 👨‍👩‍👧

7. Web Development 🌐
- Flask 🍼: Start with a micro web framework.
- Django 🦄: Dive into a full-fledged web framework.

8. Data Science and Machine Learning 🧠
- NumPy 📊: Numerical operations.
- Pandas 🐼: Data manipulation and analysis.
- Matplotlib 📈 and Seaborn 📊: Data visualization.
- Scikit-learn 🤖: Machine learning.

9. Automation and Scripting 🤖
- Automate Tasks 🛠️: Use Python to automate repetitive tasks.
- APIs 🌐: Interact with web services.

10. Testing and Debugging 🐞
- Unit Testing 🧪: Write tests for your code.
- Debugging 🔍: Learn to debug efficiently.

11. Advanced Topics 🚀
- Concurrency and Parallelism 🕒
- Decorators 🌀 and Generators ⚙️
- Web Scraping 🕸️: Extract data from websites using BeautifulSoup and Scrapy.

12. Practice Projects 💡
- Calculator 🧮
- To-Do List App 📋
- Weather App ☀️
- Personal Blog 📝

13. Community and Collaboration 🤝
- Contribute to Open Source 🌍
- Join Coding Communities 💬
- Participate in Hackathons 🏆

14. Keep Learning and Improving 📈
- Read Books 📖: Like "Automate the Boring Stuff with Python".
- Watch Tutorials 🎥: Follow video courses and tutorials.
- Solve Challenges 🧩: On platforms like LeetCode, HackerRank, and CodeWars.

15. Teach and Share Knowledge 📢
- Write Blogs ✍️
- Create Video Tutorials 📹
- Mentor Others 👨‍🏫

Hope you'll like it

Like this post if you need more resources like this 👍❤️

If this helps.


Don't forget to comment.


https://www.linkedin.com/pulse/how-can-you-build-personal-brand-become-thought-leader-akansha-yadav-71qvc?utm_source=share&utm_medium=member_android&utm_campaign=share_via


😍!! 👍🏻

Here's the link for the complete pdf of 100 pages, for those who want to learn statistics for FREE for Machine Learning role.

https://topmate.io/codingdidi/1177807


😍😍✅

https://www.instagram.com/reel/C_M7GNXyHFk/?utm_source=ig_web_copy_link&igsh=MzRlODBiNWFlZA==

https://youtu.be/80c-S7vrSAM?si=nPHKoLYsdVmMJSTy


Watch watch!!

Many people reached out to me saying telegram may get banned in their countries. So I've decided to create WhatsApp channel 👇👇


Follow the CODING DIDI channel on WhatsApp:

https://whatsapp.com/channel/0029VaiVMpH2kNFyMWeMDV2Z

Don’t worry Guys your contact number will stay hidden!

ENJOY LEARNING 👍👍

🚨Here's an opportunity for you⚠️

*Webinar highlights:-*

✓ Data acquisition
✓ Data cleaning
✓ Data analysis
✓ Data visualization
✓ Dashboard creation
✓ Story creation

*Tools that will be covered in the webinar:-*

👉🏻Python
👉🏻Mysql
👉🏻Powerbi

*Goal of the webinar:-*
✅A complete data analyst project.
✅A good decision maker.
✅Practical real world project.


*ADD ONS*:-

- Pandas notes 🗒️ which is worth rupees 299/-
- Statistics notes
- ⁠Power BI guide
- ⁠Data analysis notes
- ⁠Sql notes
- ⁠Power Bi 7 days live session access, early bird access.

*Highlights*:-
- 3 hours live session.
- access to the recording for 2 months


*Here's how you can enroll!!*
- Pay 249/- INR
- Fill out the Google form.

*Date:-* 22nd sept 2024
*Timing:-* 7 pm - 10 pm IST

FREE RESOURCES TO LEARN PYTHON
👇👇

Free Udacity Course to learn Python

https://imp.i115008.net/5bK93j

Data Structure and OOPS in Python Free Courses

https://bit.ly/3t1WEBt

Free Certified Python course by Freecodecamp

https://www.freecodecamp.org/learn/scientific-computing-with-python/

Free Python Course from Google

https://developers.google.com/edu/python

Free Python Tutorials from Kaggle

https://www.kaggle.com/learn/python

Python hands-on Project

https://t.me/Programming_experts/23

Free Python Books Collection

https://cfm.ehu.es/ricardo/docs/python/Learning_Python.pdf

https://static.realpython.com/python-basics-sample-chapters.pdf

👨‍💻Websites to Practice Python

1. http://codingbat.com/python
2. https://www.hackerrank.com/
3. https://www.hackerearth.com/practice/
4. https://projecteuler.net/archives
5. http://www.codeabbey.com/index/task_list
6. http://www.pythonchallenge.com/

Beginner's guide to Python Free Book

https://t.me/pythondevelopersindia/144

Official Documentation

https://docs.python.org/3/

ENJOY LEARNING 👍👍

🚨Here's an opportunity for you⚠️

*Webinar highlights:-*

✓ Data acquisition
✓ Data cleaning
✓ Data analysis
✓ Data visualization
✓ Dashboard creation
✓ Story creation

*Tools that will be covered in the webinar:-*

👉🏻Python
👉🏻Mysql
👉🏻Powerbi

*Goal of the webinar:-*
✅A complete data analyst project.
✅A good decision maker.
✅Practical real world project.


*ADD ONS*:-

- Pandas notes 🗒️ which is worth rupees 299/-
- Statistics notes
- ⁠Power BI guide
- ⁠Data analysis notes
- ⁠Sql notes
- ⁠Power Bi 7 days live session access, early bird access.

*Highlights*:-
- 3 hours live session.
- access to the recording for 2 months


*Here's how you can enroll!!*
- Pay 249/- INR
- Fill out the Google form.

*Date:-* 22nd sept 2024
*Timing:-* 7 pm - 10 pm IST

Those who are willing to join:-

Fill the following form.
https://forms.gle/hEFVofAuJNXNRFhE8

Here’s the link for the pdf of *PYTHON hand written notes* :-

https://drive.google.com/file/d/1wBEz2Nt9s3pjIRdRIxZpUrwclX8Lt-hg/view?usp=drivesdk

Don’t forget to thank me in the comments.

Alert 🚨 😲

Many people reached out to me saying telegram may get banned in their countries. So I've decided to create a WhatsApp channel 👇👇


Follow the CODING DIDI channel on WhatsApp:

https://whatsapp.com/channel/0029VaiVMpH2kNFyMWeMDV2Z

Don’t worry Guys your contact number will stay hidden!

ENJOY LEARNING 👍👍

JPMorgan is hiring!
Position: Analyst/ Junior Analyst
Qualification: Bachelor’s/ Master’s Degree/ Undergraduate
Salary: 5 - 8 LPA (Expected)
Experience: Freshers/ Experienced
Location: Hyderabad; Bengaluru; Mumbai, India

📌Apply Now: https://jpmc.fa.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1001/job/210546045?keyword=Analyst&location=India&locationId=300000000289360&locationLevel=country&mode=location

https://jpmc.fa.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1001/job/210540888

https://jpmc.fa.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1001/requisitions/preview/210547435/?keyword=Analyst&location=India&locationId=300000000289360&locationLevel=country&mode=location


Like for more ❤️

All the best 👍👍

https://www.linkedin.com/posts/akansha-yadav24_100-dbms-questions-activity-7239652499761086465-gJbH?utm_source=share&utm_medium=member_android


100 DBMS interview Questions

10 commonly asked data science interview questions along with their answers

1️⃣ What is the difference between supervised and unsupervised learning?
Supervised learning involves learning from labeled data to predict outcomes while unsupervised learning involves finding patterns in unlabeled data.

2️⃣ Explain the bias-variance tradeoff in machine learning.
The bias-variance tradeoff is a key concept in machine learning. Models with high bias have low complexity and over-simplify, while models with high variance are more complex and over-fit to the training data. The goal is to find the right balance between bias and variance.

3️⃣ What is the Central Limit Theorem and why is it important in statistics?
The Central Limit Theorem (CLT) states that the sampling distribution of the sample means will be approximately normally distributed regardless of the underlying population distribution, as long as the sample size is sufficiently large. It is important because it justifies the use of statistics, such as hypothesis testing and confidence intervals, on small sample sizes.

4️⃣ Describe the process of feature selection and why it is important in machine learning.
Feature selection is the process of selecting the most relevant features (variables) from a dataset. This is important because unnecessary features can lead to over-fitting, slower training times, and reduced accuracy.

5️⃣ What is the difference between overfitting and underfitting in machine learning? How do you address them?
Overfitting occurs when a model is too complex and fits the training data too well, resulting in poor performance on unseen data. Underfitting occurs when a model is too simple and cannot fit the training data well enough, resulting in poor performance on both training and unseen data. Techniques to address overfitting include regularization and early stopping, while techniques to address underfitting include using more complex models or increasing the amount of input data.

6️⃣ What is regularization and why is it used in machine learning?
Regularization is a technique used to prevent overfitting in machine learning. It involves adding a penalty term to the loss function to limit the complexity of the model, effectively reducing the impact of certain features.

7️⃣ How do you handle missing data in a dataset?
Handling missing data can be done by either deleting the missing samples, imputing the missing values, or using models that can handle missing data directly.

8️⃣ What is the difference between classification and regression in machine learning?
Classification is a type of supervised learning where the goal is to predict a categorical or discrete outcome, while regression is a type of supervised learning where the goal is to predict a continuous or numerical outcome.

9️⃣ Explain the concept of cross-validation and why it is used.
Cross-validation is a technique used to evaluate the performance of a machine learning model. It involves spliting the data into training and validation sets, and then training and evaluating the model on multiple such splits. Cross-validation gives a better idea of the model's generalization ability and helps prevent over-fitting.

🔟 What evaluation metrics would you use to evaluate a binary classification model?
Some commonly used evaluation metrics for binary classification models are accuracy, precision, recall, F1 score, and ROC-AUC. The choice of metric depends on the specific requirements of the problem.


Like if you need similar content 😄👍

Hope this helps you 😊

Company name :Intent Sourcer
Job role :Data Analyst Trainee
Job type : Internship Entry level
Job Location :Nashik Division
Qualifications

Bachelor's degree or equivalent experience
Expertise with SPSS, Excel, and PowerPoint
Previous quantitative and qualitative research experience
Fresher: Less than 1 year
₹ 15K - ₹ 20K (Per Month)

Here's the link


https://www.expertia.ai/intentsourcer/job/hiring-research-analyst-643fbd5ca995c70a7045277a?utm_source=linkedin-feed&easy_apply=true&date-refresh=09/24/2024#google_vignette