𝐅𝐫𝐨𝐦 𝐃𝐚𝐭𝐚 𝐭𝐨 𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭: 𝐊𝐞𝐲 𝐒𝐤𝐢𝐥𝐥𝐬 𝐀𝐜𝐫𝐨𝐬𝐬 𝐃𝐚𝐭𝐚 𝐚𝐧𝐝 𝐌𝐋 𝐑𝐨𝐥𝐞𝐬.

📝 𝐃𝐚𝐭𝐚 𝐀𝐧𝐚𝐥𝐲𝐬𝐭 (Avg salary for a fresher: 6-8 LPA)

1. Excel
2. SQL (80% of the interview will be on expertise in SQL)
3. Python (Basic to intermediate knowledge required)
4. Data visualization tool (Most common: Tableau/PowerBI)
5. Statistics (Basic to intermediate)

📝 𝐃𝐚𝐭𝐚 𝐒𝐜𝐢𝐞𝐧𝐭𝐢𝐬𝐭 (Avg salary for a fresher: 10-15 LPA)

1. Excel, SQL, Python, Tableau/PowerBI, Statistics (All data analyst skills)
2. Mathematics (Linear algebra, Calculus)
3. Machine learning (Scikit-learn: Supervised, Unsupervised, Recommender systems, Timeseries modelling)
4. Deep learning (TensorFlow, PyTorch)
5. NLP (NLTK, spacy, gensim)

📝 𝐃𝐚𝐭𝐚 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫 (Avg salary for a fresher: 9-12 LPA)

1. Big data tools (Hadoop, Spark, Hive)
2. Python, Java or Scala
3. Data pipeline automation
4. SQL & NoSQL databases
5. ETL tools & Data warehousing (Apache Nifi, Talend, Airflow)
6. Cloud computing (AWS, Azure, GCP)

📝 𝐌𝐋 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫 (Avg salary for a fresher: 10-12 LPA)

1. Cloud platforms (AWS, Azure, GCP)
2. Machine learning
3. DevOps & CI/CD
4. Version control
5. Code optimization & Tuning

📝 𝐌𝐋𝐎𝐩𝐬 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫 (Avg salary for a fresher: 8-10 LPA)

1. CI/CD for ML Pipelines
2. Docker, Kubernetes & Container orchestration
3. Monitoring & Logging (Prometheus, Grafana, ELK stack: Elasticsearch, Logstash, Kibana)
4. Model versioning & Governance (MLflow, DVC)
5. Infrastructure as code (IaC): Teraform, CloudFormation, Ansible
6. API development & Integration
7. Automated testing for data validation, model performance & pipeline integrity

You can use ChatGPT to make money online.

Here are 10 prompts by ChatGPT

1. Develop Email Newsletters:

Make interesting email newsletters to keep audience updated and engaged.

Prompt→ "I run a local community news website. Can you help me create a weekly email newsletter that highlights key local events, stories, and updates in a compelling way?"

2. Create Online Course Material:

Make detailed and educational online course content.

Prompt→ "I'm creating an online course about basic programming for beginners. Can you help me generate a syllabus and detailed lesson plans that cover fundamental concepts in an easy-to-understand manner?"

3. Ghostwrite eBooks:

Use ChatGPT to write eBooks on different topics for online sale.

Prompt→ "I want to publish an eBook about healthy eating habits. Can you help me outline and ghostwrite the chapters, focusing on practical tips and easy recipes?"

4. Compose Music Reviews or Critiques:

Use ChatGPT to write detailed reviews of music, albums, and artists.

Prompt: "I run a music review blog. Can you help me write a detailed review of the latest album by [Artist Name], focusing on their musical style, lyrics, and overall impact?"

5. Develop Mobile App Content:

Use ChatGPT to create mobile app content like descriptions, guides, and FAQs.

Prompt: "I'm developing a fitness app and need help writing the app description for the store, user instructions, and a list of frequently asked questions."

6. Create Resume Templates:

Use ChatGPT to create diverse resume templates for various jobs.

Prompt→ "I want to offer a range of professional resume templates on my website. Can you help me create five different templates, each tailored to a specific career field like IT, healthcare, and marketing?"

7. Write Travel Guides:

Use ChatGPT to write travel guides with tips and itineraries for different places.

Prompt→ "I'm creating a travel blog about European cities. Can you help me write a comprehensive guide for first-time visitors to Paris, including must-see sights, local dining recommendations, and travel tips?"

8. Draft Legal Documents:

Use ChatGPT to write basic legal documents like contracts and terms of service.

Prompt→ "I need to draft a terms of service document for my new e-commerce website. Can you help me create a draft that covers all necessary legal points in clear language?"

9. Write Video Game Reviews:

Use ChatGPT to write engaging video game reviews, covering gameplay and graphics.

Prompt→ "I run a gaming blog. Can you help me write a detailed review of the latest [Game Title], focusing on its gameplay mechanics, storyline, and graphics quality?"

10. Develop Personal Branding Materials:

Use ChatGPT to help build a personal branding package, including bios, LinkedIn profiles, and website content.

Prompt→ "I'm a freelance graphic designer looking to strengthen my personal brand. Can you help me write a compelling biography, update my LinkedIn profile, and create content for my portfolio website?"

ENJOY LEARNING 👍👍

Copy & paste these 7 ChatGPT prompts to create an irresistible Resume/CV 👇

Showcase your strengths. Turn applications into interview invites!

Use these 10 proven ChatGPT prompts:


📈 Prompt 1: ATS Keyword Optimizer

Analyze the job description for [Position] and my resume. Identify 10 crucial keywords. Suggest natural placements in my resume, ensuring ATS compatibility. Present results as a table with Keyword, Relevance Score (1-10), and Suggested Placement. My resume: [Paste Resume]. Job description: [Paste Description].


📈 Prompt 2: Experience Section Enhancer

Optimize the bullet points for my most recent role as [Job Title]. Focus on achievements, skills utilized, and quantifiable results. Use strong action verbs. Present a before/after comparison with explanations for changes. Current job description: [Paste Current Bullets]. 


📈 Prompt 3: Skills Hierarchy Creator

Evaluate my skills for [Job Description]. Create a skills hierarchy with 3 tiers: core, advanced, and distinguishing skills. Suggest how to demonstrate each skill briefly. Present a visual skills pyramid with examples. My resume: [Paste Resume]. Job requirements: [Paste Requirements].


📈 Prompt 4: Professional Summary Crafter

Write a compelling professional summary for my resume for [Job Title]. Incorporate my unique value proposition, key skills, and career experience. Limit to 3-4 sentences. Provide 3 versions: conservative, balanced, and bold. My resume: [Paste Resume]. Job description: [Paste Description].


📈 Prompt 5:  Education Optimizer

Refine my education section for [Job Title]. Highlight relevant coursework, projects, or academic achievements. Suggest how to present ongoing education/certifications effectively. Provide a before/after version with explanations. My resume: [Paste Resume]. Job description: [Paste Description].


📈 Prompt 6: Technical Skills Showcase

List my technical skills for [Industry/Role]. Create a visual representation (Described in Text) that organizes these skills by proficiency level and relevance to [Target Role]. Suggestion skills to acquire/improve. My resume: [Paste Resume]. Job description: [Paste Description].


📈 Prompt 7:  Positive Career Gap Framing

Write an explanation for my [X months/years] career gap between [Start Date] and [End Date]. Focus on growth, skills gained, and valuable experiences. Show how these enhance my fit for [Target Job Title]. Create 3 versions for resume, cover letter, and interview response. My resume: [Paste Resume]. Job description: [Paste Job Description].

Join for more: https://t.iss.one/aiindi

#aiprompt

🚨 Google to implement AI for age verification

Google is introducing an AI-powered age verification system across its services, including YouTube, to better enforce age restrictions. This machine learning model will assess whether users are above or below 18 years old to ensure appropriate content filtering.

The initiative comes in response to increasing regulatory demands for enhanced child safety online and is part of Google's wider strategy to embed AI technologies throughout its platforms. The rollout will initially target key markets, with plans for a global expansion in the future.

Learn for free ✅

HTML — https://www.w3schools.com/html
CSS — https://CSS-tricks.com
JavaScript — https://LearnJavaScript.online
DSA --- https://t.iss.one/dsabooks/21
Git, GitHub -- https://LearnGitBranching.js.org
React — https://React-tutorial.app
API — https://RapidAPI.com/comics
SQL — https://SQLbolt.com
Python -- https://t.iss.one/pythondevelopersindia/76
PHP --- https://bit.ly/3QkY3wW
ML -- https://developers.google.com/machine-learning/crash-course
AI -- https://microsoft.github.io/AI-For-Beginners

ENJOY LEARNING 👍👍

Data Analytics Roadmap
|
|-- Fundamentals
|   |-- Mathematics
|   |   |-- Descriptive Statistics
|   |   |-- Inferential Statistics
|   |   |-- Probability Theory
|   |
|   |-- Programming
|   |   |-- Python (Focus on Libraries like Pandas, NumPy)
|   |   |-- R (For Statistical Analysis)
|   |   |-- SQL (For Data Extraction)
|
|-- Data Collection and Storage
|   |-- Data Sources
|   |   |-- APIs
|   |   |-- Web Scraping
|   |   |-- Databases
|   |
|   |-- Data Storage
|   |   |-- Relational Databases (MySQL, PostgreSQL)
|   |   |-- NoSQL Databases (MongoDB, Cassandra)
|   |   |-- Data Lakes and Warehousing (Snowflake, Redshift)
|
|-- Data Cleaning and Preparation
|   |-- Handling Missing Data
|   |-- Data Transformation
|   |-- Data Normalization and Standardization
|   |-- Outlier Detection
|
|-- Exploratory Data Analysis (EDA)
|   |-- Data Visualization Tools
|   |   |-- Matplotlib
|   |   |-- Seaborn
|   |   |-- ggplot2
|   |
|   |-- Identifying Trends and Patterns
|   |-- Correlation Analysis
|
|-- Advanced Analytics
|   |-- Predictive Analytics (Regression, Forecasting)
|   |-- Prescriptive Analytics (Optimization Models)
|   |-- Segmentation (Clustering Techniques)
|   |-- Sentiment Analysis (Text Data)
|
|-- Data Visualization and Reporting
|   |-- Visualization Tools
|   |   |-- Power BI
|   |   |-- Tableau
|   |   |-- Google Data Studio
|   |
|   |-- Dashboard Design
|   |-- Interactive Visualizations
|   |-- Storytelling with Data
|
|-- Business Intelligence (BI)
|   |-- KPI Design and Implementation
|   |-- Decision-Making Frameworks
|   |-- Industry-Specific Use Cases (Finance, Marketing, HR)
|
|-- Big Data Analytics
|   |-- Tools and Frameworks
|   |   |-- Hadoop
|   |   |-- Apache Spark
|   |
|   |-- Real-Time Data Processing
|   |-- Stream Analytics (Kafka, Flink)
|
|-- Domain Knowledge
|   |-- Industry Applications
|   |   |-- E-commerce
|   |   |-- Healthcare
|   |   |-- Supply Chain
|
|-- Ethical Data Usage
|   |-- Data Privacy Regulations (GDPR, CCPA)
|   |-- Bias Mitigation in Analysis
|   |-- Transparency in Reporting

Free Resources to learn Data Analytics skills👇👇

1. SQL

https://mode.com/sql-tutorial/introduction-to-sql

https://t.iss.one/sqlspecialist/738

2. Python

https://www.learnpython.org/

https://t.iss.one/pythondevelopersindia/873

https://bit.ly/3T7y4ta

https://www.geeksforgeeks.org/python-programming-language/learn-python-tutorial

3. R

https://datacamp.pxf.io/vPyB4L

4. Data Structures

https://leetcode.com/study-plan/data-structure/

https://www.udacity.com/course/data-structures-and-algorithms-in-python--ud513

5. Data Visualization

https://www.freecodecamp.org/learn/data-visualization/

https://t.iss.one/Data_Visual/2

https://www.tableau.com/learn/training/20223

https://www.workout-wednesday.com/power-bi-challenges/

6. Excel

https://excel-practice-online.com/

https://t.iss.one/excel_data

https://www.w3schools.com/EXCEL/index.php

Join @free4unow_backup for more free courses

Like for more ❤️

ENJOY LEARNING 👍👍

Advanced SQL Optimization Tips for Data Analysts

1. Use Proper Indexing
Create indexes on frequently queried columns to speed up data retrieval.

2. Avoid `SELECT *`
Specify only the columns you need to reduce the amount of data processed.

3. Use `WHERE` Instead of `HAVING`
Filter your data as early as possible in the query to optimize performance.

4. Limit Joins
Try to keep joins to a minimum to reduce query complexity and processing time.

5. Apply `LIMIT` or `TOP`
Retrieve only the required rows to save on resources.

6. Optimize Joins
Use INNER JOIN instead of OUTER JOIN whenever possible.

7. Use Temporary Tables
Break large, complex queries into smaller parts using temporary tables.

8. Avoid Functions on Indexed Columns
Using functions on indexed columns often prevents the index from being used.

9. Use CTEs for Readability
Common Table Expressions help simplify nested queries and improve clarity.

10. Analyze Execution Plans
Leverage execution plans to identify bottlenecks and make targeted optimizations.

Happy querying!

⌨️ Benefits of learning Python Programming

1. Web Development: Python frameworks like Django and Flask are popular for building dynamic websites and web applications.

2. Data Analysis: Python has powerful libraries like Pandas and NumPy for data manipulation and analysis, making it widely used in data science and analytic.

3. Machine Learning: Python's libraries such as TensorFlow, Keras, and Scikit-learn are extensively used for implementing machine learning algorithms and building predictive models.

4. Artificial Intelligence: Python is commonly used in AI development due to its simplicity and extensive libraries for tasks like natural language processing, image recognition, and neural network implementation.

5. Cybersecurity: Python is utilized for tasks such as penetration testing, network scanning, and creating security tools due to its versatility and ease of use.

6. Game Development: Python, along with libraries like Pygame, is used for developing games, prototyping game mechanics, and creating game scripts.

7. Automation: Python's simplicity and versatility make it ideal for automating repetitive tasks, such as scripting, data scraping, and process automation.

𝐇𝐨𝐰 𝐭𝐨 𝐢𝐦𝐩𝐫𝐨𝐯𝐞 𝐝𝐚𝐭𝐚𝐛𝐚𝐬𝐞 𝐩𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞?

Here are some of the top ways to improve database performance:

1. Indexing
Create the right indexes based on query patterns to speed up data retrieval.

2. Materialized Views
Store pre-computed query results for quick access, reducing the need to process complex queries repeatedly.

3. Vertical Scaling
Increase the capacity of the hashtag#database server by adding more CPU, RAM, or storage.

Old AI models are losing their minds— Literally

Scientists gave AI chatbots a real human dementia test (the MoCA), and guess what? The older ones basically drooled on the exam. ChatGPT-4 barely passed with a 26/30, but Gemini 1.0 scored a tragic 16—worse than your sleep-deprived grandpa.

Turns out, AI struggles with visual/spatial tasks, executive function, and, uh… remembering things. So if an AI tells you it’s “99% sure” you have the plague, maybe get a second opinion—from an actual doctor.

How to start your career in data analysis for freshers 😄👇

1. Learn the Basics: Begin with understanding the fundamental concepts of statistics, mathematics, and programming languages like Python or R.

Free Resources: https://t.iss.one/pythonanalyst/103

2. Acquire Technical Skills: Develop proficiency in data analysis tools such as Excel, SQL, and data visualization tools like Tableau or Power BI.

Free Data Analysis Books: https://t.iss.one/learndataanalysis

3. Gain Knowledge in Statistics: A solid foundation in statistical concepts is crucial for data analysis. Learn about probability, hypothesis testing, and regression analysis.
Free course by Khan Academy will help you to enhance these skills.

4. Programming Proficiency: Enhance your programming skills, especially in languages commonly used in data analysis like Python or R. Familiarity with libraries such as Pandas and NumPy in Python is beneficial. Kaggle has amazing content to learn these skills.

5. Data Cleaning and Preprocessing: Understand the importance of cleaning and preprocessing data. Learn techniques to handle missing values, outliers, and transform data for analysis.

6. Database Knowledge: Acquire knowledge about databases and SQL for efficient data retrieval and manipulation.
SQL for data analytics: https://t.iss.one/sqlanalyst

7. Data Visualization: Master the art of presenting insights through visualizations. Learn tools like Matplotlib, Seaborn, or ggplot2 for creating meaningful charts and graphs. If you are from non-technical background, learn Tableau or Power BI.
FREE Resources to learn data visualization: https://t.iss.one/PowerBI_analyst

8. Machine Learning Basics: Familiarize yourself with basic machine learning concepts. This knowledge can be beneficial for advanced analytics tasks.
ML Basics: https://t.iss.one/datasciencefun/1476

9. Build a Portfolio: Work on projects that showcase your skills. This could be personal projects, contributions to open-source projects, or challenges from platforms like Kaggle.
Data Analytics Portfolio Projects: https://t.iss.one/DataPortfolio

10. Networking and Continuous Learning: Engage with the data science community, attend meetups, webinars, and conferences. Build your strong Linkedin profile and enhance your network.

11. Apply for Internships or Entry-Level Positions: Gain practical experience by applying for internships or entry-level positions in data analysis. Real-world projects contribute significantly to your learning.
Data Analyst Jobs & Internship opportunities: https://t.iss.one/jobs_SQL

12. Effective Communication: Develop strong communication skills. Being able to convey your findings and insights in a clear and understandable manner is crucial.

Share with credits: https://t.iss.one/sqlspecialist

Hope it helps :)