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❤1
Essential Python topics for data analysts 👇
Python Topics:
1. Data Structures
- Lists, Tuples, and Dictionaries
- NumPy Arrays for numerical data
2. Data Manipulation
- Pandas DataFrames for structured data
- Data Cleaning and Preprocessing techniques
- Data Transformation and Reshaping
3. Data Visualization
- Matplotlib for basic plotting
- Seaborn for statistical visualizations
- Plotly for interactive charts
4. Statistical Analysis
- Descriptive Statistics
- Hypothesis Testing
- Regression Analysis
5. Machine Learning
- Scikit-Learn for machine learning models
- Model Building, Training, and Evaluation
- Feature Engineering and Selection
6. Time Series Analysis
- Handling Time Series Data
- Time Series Forecasting
- Anomaly Detection
7. Python Fundamentals
- Control Flow (if statements, loops)
- Functions and Modular Code
- Exception Handling
- File
Remember, it's highly likely that you won't know all these concepts from the start. Data analysis is a journey where the more you learn, the more you grow. Embrace the learning process, and your skills will continually evolve and expand. Keep up the great work!
Python for Machine Learning: https://t.me/pythonresourcestp/48
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Hope you'll like it
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Python Topics:
1. Data Structures
- Lists, Tuples, and Dictionaries
- NumPy Arrays for numerical data
2. Data Manipulation
- Pandas DataFrames for structured data
- Data Cleaning and Preprocessing techniques
- Data Transformation and Reshaping
3. Data Visualization
- Matplotlib for basic plotting
- Seaborn for statistical visualizations
- Plotly for interactive charts
4. Statistical Analysis
- Descriptive Statistics
- Hypothesis Testing
- Regression Analysis
5. Machine Learning
- Scikit-Learn for machine learning models
- Model Building, Training, and Evaluation
- Feature Engineering and Selection
6. Time Series Analysis
- Handling Time Series Data
- Time Series Forecasting
- Anomaly Detection
7. Python Fundamentals
- Control Flow (if statements, loops)
- Functions and Modular Code
- Exception Handling
- File
Remember, it's highly likely that you won't know all these concepts from the start. Data analysis is a journey where the more you learn, the more you grow. Embrace the learning process, and your skills will continually evolve and expand. Keep up the great work!
Python for Machine Learning: https://t.me/pythonresourcestp/48
Best Programming Resources: https://topmate.io/learning_resources/1362011
Hope you'll like it
Like this post if you need more resources like this 👍❤️
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Preparing for a data science interview can be challenging, but with the right approach, you can increase your chances of success. Here are some tips to help you prepare for your next data science interview:
👉 1. Review the Fundamentals: Make sure you have a thorough understanding of the fundamentals of statistics, probability, and linear algebra. You should also be familiar with data structures, algorithms, and programming languages like Python, R, and SQL.
👉 2. Brush up on Machine Learning: Machine learning is a key aspect of data science. Make sure you have a solid understanding of different types of machine learning algorithms like supervised, unsupervised, and reinforcement learning.
👉 3. Practice Coding: Practice coding questions related to data structures, algorithms, and data science problems. You can use online resources like HackerRank, LeetCode, and Kaggle to practice.
👉 4. Build a Portfolio: Create a portfolio of projects that demonstrate your data science skills. This can include data cleaning, data wrangling, exploratory data analysis, and machine learning projects.
👉 5. Practice Communication: Data scientists are expected to effectively communicate complex technical concepts to non-technical stakeholders. Practice explaining your projects and technical concepts in simple terms.
👉 6. Research the Company: Research the company you are interviewing with and their industry. Understand how they use data and what data science problems they are trying to solve.
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Free Notes & Books to learn Data Science: https://t.me/datascienceresourcestp
Python Project Ideas: https://t.me/pythonresourcestp/74
Best Resources to learn Data Science 👇👇
Python Tutorial (http://pythontutorial.net/)
Data Science Course (http://kaggle.com/learn) by Kaggle
Machine Learning Course (http://developers.google.com/machine-learning/crash-course) by Google
Best Data Science & Machine Learning Resources (https://topmate.io/learning_resources/1406977)
Interview Process for Data Science Role at Amazon (https://t.me/datascienceresourcestp/85)
Python Interview Resources (https://t.me/pythonresourcestp/40)
Join for more free courses
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ENJOY LEARNING👍👍
Join Our WhatsApp Channel:
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👉 1. Review the Fundamentals: Make sure you have a thorough understanding of the fundamentals of statistics, probability, and linear algebra. You should also be familiar with data structures, algorithms, and programming languages like Python, R, and SQL.
👉 2. Brush up on Machine Learning: Machine learning is a key aspect of data science. Make sure you have a solid understanding of different types of machine learning algorithms like supervised, unsupervised, and reinforcement learning.
👉 3. Practice Coding: Practice coding questions related to data structures, algorithms, and data science problems. You can use online resources like HackerRank, LeetCode, and Kaggle to practice.
👉 4. Build a Portfolio: Create a portfolio of projects that demonstrate your data science skills. This can include data cleaning, data wrangling, exploratory data analysis, and machine learning projects.
👉 5. Practice Communication: Data scientists are expected to effectively communicate complex technical concepts to non-technical stakeholders. Practice explaining your projects and technical concepts in simple terms.
👉 6. Research the Company: Research the company you are interviewing with and their industry. Understand how they use data and what data science problems they are trying to solve.
Learn DatA & AI: https://365datascience.pxf.io/Z6KDgk
Free Notes & Books to learn Data Science: https://t.me/datascienceresourcestp
Python Project Ideas: https://t.me/pythonresourcestp/74
Best Resources to learn Data Science 👇👇
Python Tutorial (http://pythontutorial.net/)
Data Science Course (http://kaggle.com/learn) by Kaggle
Machine Learning Course (http://developers.google.com/machine-learning/crash-course) by Google
Best Data Science & Machine Learning Resources (https://topmate.io/learning_resources/1406977)
Interview Process for Data Science Role at Amazon (https://t.me/datascienceresourcestp/85)
Python Interview Resources (https://t.me/pythonresourcestp/40)
Join for more free courses
https://t.me/techpsyche
Like for more ❤️
ENJOY LEARNING👍👍
Join Our WhatsApp Channel:
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
The economy is a priority for many. A recent poll indicates people's concerns about rising costs and financial stability. Stay tuned for expert insights and tips on navigating these challenges! 💰📊
t.me/techpsyche
t.me/techpsyche
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Google Advanced Data Analytics
◾️https://www.coursera.org/professional-certificates/google-advanced-data-analytics
Google Crash Course on Python
◾️https://www.coursera.org/learn/python-crash-course
Artificial Intelligence (AI)
◾️https://www.coursera.org/learn/introduction-to-ai
IBM Data Science
◾️https://www.coursera.org/professional-certificates/ibm-data-science
Natural Language Processing Specialization
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Deep Learning Specialization
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Machine Learning Specialization
◽️https://www.coursera.org/specializations/machine-learning-introduction
IBM Python for Data Science, AI & Development
◾️https://www.coursera.org/learn/python-for-applied-data-science-ai
Meta Front-End Developer
◽️https://www.coursera.org/professional-certificates/meta-front-end-developer
Learn Python Basics for Data Analysis
◾️https://www.coursera.org/learn/data-analysis-with-python
NVIDIA FREE AI Certification Courses
https://tinyurl.com/5hessh3t
Top 7 FREE Courses By Udacity
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Free PHP Courses for Web Developer
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CISCO Free Certification Courses
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Should I post both Jobs from Different Countries and Remote Jobs OR Only Remote Jobs?
Anonymous Poll
75%
Both (From Countries & Remote)
25%
Only Remote
Remote Website Developer Job at Adventure Travel 365
Location: Fully Remote (Anywhere in the World)
Company Headquarters: Phoenix, Arizona, United States
Commitment: Part-Time
- HTML, CSS, JavaScript
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Location: Fully Remote (Anywhere in the World)
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Commitment: Part-Time
- HTML, CSS, JavaScript
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- Graphics design skill is a plus
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✳️ Hᴏᴡ Sᴏᴄɪᴀʟ Eɴɢɪɴᴇᴇʀɪɴɢ Wᴏʀᴋs?
🌀ɢᴀᴛʜᴇʀ ɪɴғᴏʀᴍᴀᴛɪᴏɴ: ᴛʜɪs ɪs ᴛʜᴇ ғɪʀsᴛ sᴛᴀɢᴇ, ʜᴇ ʟᴇᴀʀɴs ᴀs ᴍᴜᴄʜ ᴀs ʜᴇ ᴄᴀɴ ᴀʙᴏᴜᴛ ᴛʜᴇ ɪɴᴛᴇɴᴅᴇᴅ ᴠɪᴄᴛɪᴍ. ᴛʜᴇ ɪɴғᴏʀᴍᴀᴛɪᴏɴ ɪs ɢᴀᴛʜᴇʀᴇᴅ ғʀᴏᴍ ᴄᴏᴍᴘᴀɴʏ ᴡᴇʙsɪᴛᴇs, ᴏᴛʜᴇʀ ᴘᴜʙʟɪᴄᴀᴛɪᴏɴs ᴀɴᴅ sᴏᴍᴇᴛɪᴍᴇs ʙʏ ᴛᴀʟᴋɪɴɢ ᴛᴏ ᴛʜᴇ ᴜsᴇʀs ᴏғ ᴛʜᴇ ᴛᴀʀɢᴇᴛ sʏsᴛᴇᴍ.
🌀ᴘʟᴀɴ ᴀᴛᴛᴀᴄᴋ: ᴛʜᴇ ᴀᴛᴛᴀᴄᴋᴇʀs ᴏᴜᴛʟɪɴᴇ ʜᴏᴡ ʜᴇ/sʜᴇ ɪɴᴛᴇɴᴅs ᴛᴏ ᴇxᴇᴄᴜᴛᴇ ᴛʜᴇ ᴀᴛᴛᴀᴄᴋ
🌀ᴀᴄϙᴜɪʀᴇ ᴛᴏᴏʟs: ᴛʜᴇsᴇ ɪɴᴄʟᴜᴅᴇ ᴄᴏᴍᴘᴜᴛᴇʀ ᴘʀᴏɢʀᴀᴍs ᴛʜᴀᴛ ᴀɴ ᴀᴛᴛᴀᴄᴋᴇʀ ᴡɪʟʟ ᴜsᴇ ᴡʜᴇɴ ʟᴀᴜɴᴄʜɪɴɢ ᴛʜᴇ ᴀᴛᴛᴀᴄᴋ.
🌀ᴀᴛᴛᴀᴄᴋ: ᴇxᴘʟᴏɪᴛ ᴛʜᴇ ᴡᴇᴀᴋɴᴇssᴇs ɪɴ ᴛʜᴇ ᴛᴀʀɢᴇᴛ sʏsᴛᴇᴍ.
🌀ᴜsᴇ ᴀᴄϙᴜɪʀᴇᴅ ᴋɴᴏᴡʟᴇᴅɢᴇ: ɪɴғᴏʀᴍᴀᴛɪᴏɴ ɢᴀᴛʜᴇʀᴇᴅ ᴅᴜʀɪɴɢ ᴛʜᴇ sᴏᴄɪᴀʟ ᴇɴɢɪɴᴇᴇʀɪɴɢ ᴛᴀᴄᴛɪᴄs sᴜᴄʜ ᴀs ᴘᴇᴛ ɴᴀᴍᴇs, ʙɪʀᴛʜᴅᴀᴛᴇs ᴏғ ᴛʜᴇ ᴏʀɢᴀɴɪᴢᴀᴛɪᴏɴ ғᴏᴜɴᴅᴇʀs, ᴇᴛᴄ. ɪs ᴜsᴇᴅ ɪɴ ᴀᴛᴛᴀᴄᴋs sᴜᴄʜ ᴀs ᴘᴀssᴡᴏʀᴅ ɢᴜᴇssɪɴɢ.
What is CTF & How to solve CTF: https://t.me/zerotrusthackers/75
Red Team Free Course: https://t.me/zerotrusthackers/68
Cyber Security Course for Beginners: https://udemy.com/course/certified-secure-netizen/
Google Dorks for Information Gathering: https://t.me/zerotrusthackers/54
Cyber Security Vocabulary: https://t.me/zerotrusthackers/71
Password Attacks: https://t.me/zerotrusthackers/67
More Security Resources Here:
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🌀ɢᴀᴛʜᴇʀ ɪɴғᴏʀᴍᴀᴛɪᴏɴ: ᴛʜɪs ɪs ᴛʜᴇ ғɪʀsᴛ sᴛᴀɢᴇ, ʜᴇ ʟᴇᴀʀɴs ᴀs ᴍᴜᴄʜ ᴀs ʜᴇ ᴄᴀɴ ᴀʙᴏᴜᴛ ᴛʜᴇ ɪɴᴛᴇɴᴅᴇᴅ ᴠɪᴄᴛɪᴍ. ᴛʜᴇ ɪɴғᴏʀᴍᴀᴛɪᴏɴ ɪs ɢᴀᴛʜᴇʀᴇᴅ ғʀᴏᴍ ᴄᴏᴍᴘᴀɴʏ ᴡᴇʙsɪᴛᴇs, ᴏᴛʜᴇʀ ᴘᴜʙʟɪᴄᴀᴛɪᴏɴs ᴀɴᴅ sᴏᴍᴇᴛɪᴍᴇs ʙʏ ᴛᴀʟᴋɪɴɢ ᴛᴏ ᴛʜᴇ ᴜsᴇʀs ᴏғ ᴛʜᴇ ᴛᴀʀɢᴇᴛ sʏsᴛᴇᴍ.
🌀ᴘʟᴀɴ ᴀᴛᴛᴀᴄᴋ: ᴛʜᴇ ᴀᴛᴛᴀᴄᴋᴇʀs ᴏᴜᴛʟɪɴᴇ ʜᴏᴡ ʜᴇ/sʜᴇ ɪɴᴛᴇɴᴅs ᴛᴏ ᴇxᴇᴄᴜᴛᴇ ᴛʜᴇ ᴀᴛᴛᴀᴄᴋ
🌀ᴀᴄϙᴜɪʀᴇ ᴛᴏᴏʟs: ᴛʜᴇsᴇ ɪɴᴄʟᴜᴅᴇ ᴄᴏᴍᴘᴜᴛᴇʀ ᴘʀᴏɢʀᴀᴍs ᴛʜᴀᴛ ᴀɴ ᴀᴛᴛᴀᴄᴋᴇʀ ᴡɪʟʟ ᴜsᴇ ᴡʜᴇɴ ʟᴀᴜɴᴄʜɪɴɢ ᴛʜᴇ ᴀᴛᴛᴀᴄᴋ.
🌀ᴀᴛᴛᴀᴄᴋ: ᴇxᴘʟᴏɪᴛ ᴛʜᴇ ᴡᴇᴀᴋɴᴇssᴇs ɪɴ ᴛʜᴇ ᴛᴀʀɢᴇᴛ sʏsᴛᴇᴍ.
🌀ᴜsᴇ ᴀᴄϙᴜɪʀᴇᴅ ᴋɴᴏᴡʟᴇᴅɢᴇ: ɪɴғᴏʀᴍᴀᴛɪᴏɴ ɢᴀᴛʜᴇʀᴇᴅ ᴅᴜʀɪɴɢ ᴛʜᴇ sᴏᴄɪᴀʟ ᴇɴɢɪɴᴇᴇʀɪɴɢ ᴛᴀᴄᴛɪᴄs sᴜᴄʜ ᴀs ᴘᴇᴛ ɴᴀᴍᴇs, ʙɪʀᴛʜᴅᴀᴛᴇs ᴏғ ᴛʜᴇ ᴏʀɢᴀɴɪᴢᴀᴛɪᴏɴ ғᴏᴜɴᴅᴇʀs, ᴇᴛᴄ. ɪs ᴜsᴇᴅ ɪɴ ᴀᴛᴛᴀᴄᴋs sᴜᴄʜ ᴀs ᴘᴀssᴡᴏʀᴅ ɢᴜᴇssɪɴɢ.
What is CTF & How to solve CTF: https://t.me/zerotrusthackers/75
Red Team Free Course: https://t.me/zerotrusthackers/68
Cyber Security Course for Beginners: https://udemy.com/course/certified-secure-netizen/
Google Dorks for Information Gathering: https://t.me/zerotrusthackers/54
Cyber Security Vocabulary: https://t.me/zerotrusthackers/71
Password Attacks: https://t.me/zerotrusthackers/67
More Security Resources Here:
https://whatsapp.com/channel/0029VaxVv551iUxRku094918
Forwarded from Web Development Resources TP
Forwarded from SQL Resources TP
𝟱 𝗦𝗤𝗟 𝗠𝘆𝘁𝗵𝘀 𝗗𝗲𝗯𝘂𝗻𝗸𝗲𝗱 ❌ 𝗪𝗵𝗮𝘁 𝗕𝗲𝗴𝗶𝗻𝗻𝗲𝗿𝘀 𝗢𝗳𝘁𝗲𝗻 𝗚𝗲𝘁 𝗪𝗿𝗼𝗻𝗴
SQL is super powerful, but some myths around it can trip up beginners. Let’s clear up five common misunderstandings and set the record straight:
𝗠𝘆𝘁𝗵 𝟭: 𝗦𝗤𝗟 𝗶𝘀 𝗷𝘂𝘀𝘁 𝗳𝗼𝗿 𝗽𝘂𝗹𝗹𝗶𝗻𝗴 𝗱𝗮𝘁𝗮.
✦ 𝗥𝗲𝗮𝗹𝗶𝘁𝘆: Nope, it’s not just for that! SQL can also create, modify, and manage databases, control access, and maintain data consistency.
✦ 𝗙𝗶𝘅 𝗶𝘁: Explore all the features of SQL, like DDL (for database design), DCL (for access control), and TCL (for transactions). It's more than just SELECT!
𝗠𝘆𝘁𝗵 𝟮: 𝗨𝘀𝗶𝗻𝗴 𝗦𝗘𝗟𝗘𝗖𝗧 * 𝗶𝘀 𝗳𝗶𝗻𝗲.
✦ 𝗥𝗲𝗮𝗹𝗶𝘁𝘆: It might be easy, but it’s not efficient. Pulling all columns wastes memory and slows down performance.
✦ 𝗙𝗶𝘅 𝗶𝘁: Only select the columns you actually need. It’s faster and cleaner.
Not great - SELECT * FROM employees;
Better - SELECT employee_id, name, department FROM employees;
𝗠𝘆𝘁𝗵 𝟯: 𝗦𝗤𝗟 𝗰𝗮𝗻'𝘁 𝗵𝗮𝗻𝗱𝗹𝗲 𝗰𝗼𝗺𝗽𝗹𝗲𝘅 𝗮𝗻𝗮𝗹𝘆𝘀𝗶𝘀.
✦ 𝗥𝗲𝗮𝗹𝗶𝘁𝘆: SQL can do way more than basic queries! With concepts like window functions and CTEs, you can handle really complex data analysis.
✦ 𝗙𝗶𝘅 𝗶𝘁: Learn advanced SQL features like window functions (ROW_NUMBER(), RANK()) and CTEs to up your game.
Example - Ranking employees by salary within their department
WITH ranked_salaries AS (SELECT employee_id, salary, department,
ROW_NUMBER() OVER (PARTITION BY department ORDER BY salary DESC) AS rank FROM employees)
SELECT * FROM ranked_salaries WHERE rank = 1;
𝗠𝘆𝘁𝗵 𝟰: 𝗦𝗹𝗼𝘄 𝗾𝘂𝗲𝗿𝗶𝗲𝘀 𝗮𝗿𝗲 𝗮𝗹𝘄𝗮𝘆𝘀 𝘁𝗵𝗲 𝗱𝗮𝘁𝗮𝗯𝗮𝘀𝗲’𝘀 𝗳𝗮𝘂𝗹𝘁.
✦ 𝗥𝗲𝗮𝗹𝗶𝘁𝘆: It’s usually inefficient queries causing the slowdown. Things like missing indexes or unoptimized code can be the culprit.
✦ 𝗙𝗶𝘅 𝗶𝘁: Use indexes properly, avoid complex calculations in WHERE clauses, and check your query execution plan to spot bottlenecks.
𝗠𝘆𝘁𝗵 𝟱: 𝗦𝗤𝗟 𝗶𝘀 𝗼𝘂𝘁𝗱𝗮𝘁𝗲𝗱 𝗮𝗻𝗱 𝘄𝗶𝗹𝗹 𝗯𝗲 𝗿𝗲𝗽𝗹𝗮𝗰𝗲𝗱 𝘀𝗼𝗼𝗻.
✦ 𝗥𝗲𝗮𝗹𝗶𝘁𝘆: SQL is here to stay! Despite the rise of NoSQL, SQL remains the backbone for structured data.
✦ 𝗙𝗶𝘅 𝗶𝘁: Stay current and explore how SQL integrates with big data platforms and cloud databases. It’s more relevant than ever.
Don’t let these myths hold you back. SQL is powerful, and when you understand it fully, you can do amazing things with your data.
SQL Relational Database Free Course Here: https://tinyurl.com/42nau8jx
Learn & Practice SQL (https://bit.ly/4kNb15x)
SQL Topics for Data Analysts (https://t.me/sqlresourcestp/83)
SQL Udacity Course (https://udacity.com/course/sql-for-data-analysis--ud198)
Download SQL Cheatsheet (https://t.me/sqlresourcestp/4)
Also try to apply what you learn through hands-on projects or challenges.
ENJOY LEARNING 👍👍
More Resources Here
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
Like this post if you need more 👍❤️
Hope it helps :)
SQL is super powerful, but some myths around it can trip up beginners. Let’s clear up five common misunderstandings and set the record straight:
𝗠𝘆𝘁𝗵 𝟭: 𝗦𝗤𝗟 𝗶𝘀 𝗷𝘂𝘀𝘁 𝗳𝗼𝗿 𝗽𝘂𝗹𝗹𝗶𝗻𝗴 𝗱𝗮𝘁𝗮.
✦ 𝗥𝗲𝗮𝗹𝗶𝘁𝘆: Nope, it’s not just for that! SQL can also create, modify, and manage databases, control access, and maintain data consistency.
✦ 𝗙𝗶𝘅 𝗶𝘁: Explore all the features of SQL, like DDL (for database design), DCL (for access control), and TCL (for transactions). It's more than just SELECT!
𝗠𝘆𝘁𝗵 𝟮: 𝗨𝘀𝗶𝗻𝗴 𝗦𝗘𝗟𝗘𝗖𝗧 * 𝗶𝘀 𝗳𝗶𝗻𝗲.
✦ 𝗥𝗲𝗮𝗹𝗶𝘁𝘆: It might be easy, but it’s not efficient. Pulling all columns wastes memory and slows down performance.
✦ 𝗙𝗶𝘅 𝗶𝘁: Only select the columns you actually need. It’s faster and cleaner.
Not great - SELECT * FROM employees;
Better - SELECT employee_id, name, department FROM employees;
𝗠𝘆𝘁𝗵 𝟯: 𝗦𝗤𝗟 𝗰𝗮𝗻'𝘁 𝗵𝗮𝗻𝗱𝗹𝗲 𝗰𝗼𝗺𝗽𝗹𝗲𝘅 𝗮𝗻𝗮𝗹𝘆𝘀𝗶𝘀.
✦ 𝗥𝗲𝗮𝗹𝗶𝘁𝘆: SQL can do way more than basic queries! With concepts like window functions and CTEs, you can handle really complex data analysis.
✦ 𝗙𝗶𝘅 𝗶𝘁: Learn advanced SQL features like window functions (ROW_NUMBER(), RANK()) and CTEs to up your game.
Example - Ranking employees by salary within their department
WITH ranked_salaries AS (SELECT employee_id, salary, department,
ROW_NUMBER() OVER (PARTITION BY department ORDER BY salary DESC) AS rank FROM employees)
SELECT * FROM ranked_salaries WHERE rank = 1;
𝗠𝘆𝘁𝗵 𝟰: 𝗦𝗹𝗼𝘄 𝗾𝘂𝗲𝗿𝗶𝗲𝘀 𝗮𝗿𝗲 𝗮𝗹𝘄𝗮𝘆𝘀 𝘁𝗵𝗲 𝗱𝗮𝘁𝗮𝗯𝗮𝘀𝗲’𝘀 𝗳𝗮𝘂𝗹𝘁.
✦ 𝗥𝗲𝗮𝗹𝗶𝘁𝘆: It’s usually inefficient queries causing the slowdown. Things like missing indexes or unoptimized code can be the culprit.
✦ 𝗙𝗶𝘅 𝗶𝘁: Use indexes properly, avoid complex calculations in WHERE clauses, and check your query execution plan to spot bottlenecks.
𝗠𝘆𝘁𝗵 𝟱: 𝗦𝗤𝗟 𝗶𝘀 𝗼𝘂𝘁𝗱𝗮𝘁𝗲𝗱 𝗮𝗻𝗱 𝘄𝗶𝗹𝗹 𝗯𝗲 𝗿𝗲𝗽𝗹𝗮𝗰𝗲𝗱 𝘀𝗼𝗼𝗻.
✦ 𝗥𝗲𝗮𝗹𝗶𝘁𝘆: SQL is here to stay! Despite the rise of NoSQL, SQL remains the backbone for structured data.
✦ 𝗙𝗶𝘅 𝗶𝘁: Stay current and explore how SQL integrates with big data platforms and cloud databases. It’s more relevant than ever.
Don’t let these myths hold you back. SQL is powerful, and when you understand it fully, you can do amazing things with your data.
SQL Relational Database Free Course Here: https://tinyurl.com/42nau8jx
Learn & Practice SQL (https://bit.ly/4kNb15x)
SQL Topics for Data Analysts (https://t.me/sqlresourcestp/83)
SQL Udacity Course (https://udacity.com/course/sql-for-data-analysis--ud198)
Download SQL Cheatsheet (https://t.me/sqlresourcestp/4)
Also try to apply what you learn through hands-on projects or challenges.
ENJOY LEARNING 👍👍
More Resources Here
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
Like this post if you need more 👍❤️
Hope it helps :)
What are public and private keys?
Your blockchain wallet has a “private key” and a “public key.”
You shouldn’t show or reveal the private key to anyone because it gives access to your coins.
The public key, however, can be shown to anyone.
Moreover, your public key is your wallet’s address, where coins are sent to you.
In simple terms:
The private key is the key that gives you access to your coins; the public key is the code used to receive cryptocurrency at your address.What are public and private keys?
Your blockchain wallet has a “private key” and a “public key.”
You shouldn’t show or reveal the private key to anyone because it gives access to your coins.
The public key, however, can be shown to anyone.
Moreover, your public key is your wallet’s address, where coins are sent to you.
In simple terms:
The private key is the key that gives you access to your coins; the public key is the code used to receive cryptocurrency at your address.
Funding in Crypto Trading: https://t.me/techpsyche/766
Choosing the right Exchange: https://t.me/techpsyche/774
Types of stablecoins: https://t.me/techpsyche/789
More Resources Here:
https://whatsapp.com/channel/0029VajB00n0LKZ7cSloGR1M
#crypto #web3 #blockchain #finance #stocks
Your blockchain wallet has a “private key” and a “public key.”
You shouldn’t show or reveal the private key to anyone because it gives access to your coins.
The public key, however, can be shown to anyone.
Moreover, your public key is your wallet’s address, where coins are sent to you.
In simple terms:
The private key is the key that gives you access to your coins; the public key is the code used to receive cryptocurrency at your address.What are public and private keys?
Your blockchain wallet has a “private key” and a “public key.”
You shouldn’t show or reveal the private key to anyone because it gives access to your coins.
The public key, however, can be shown to anyone.
Moreover, your public key is your wallet’s address, where coins are sent to you.
In simple terms:
The private key is the key that gives you access to your coins; the public key is the code used to receive cryptocurrency at your address.
Funding in Crypto Trading: https://t.me/techpsyche/766
Choosing the right Exchange: https://t.me/techpsyche/774
Types of stablecoins: https://t.me/techpsyche/789
More Resources Here:
https://whatsapp.com/channel/0029VajB00n0LKZ7cSloGR1M
#crypto #web3 #blockchain #finance #stocks
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Top 10 Programming Languages to learn in 2025 (With Free Resources to learn) :-
1. Python
- learnpython.org
- t.me/pythonresourcestp
2. Java
- learnjavaonline.org
- t.me/javaresourcestp
3. C#
- learncs.org
- w3schools.com
4. JavaScript
- learnjavascript.online
- t.me/javascriptresourcestp
5. Rust
- rust-lang.org
- exercism.org
6. Go Programming
- go.dev
- learn-golang.org
7. Kotlin
- kotlinlang.org
- w3schools.com/KOTLIN
8. TypeScript
- Typescriptlang.org
- learntypescript.dev
9. SQL
- datasimplifier.com
- t.me/sqlresourcestp
10. R Programming
- w3schools.com/r/
- r-coder.com
ENJOY LEARNING 👍👍
3 FREE Courses by Google, Microsoft & LinkedIn
https://tinyurl.com/3w3xu4sh
7 Free Courses by Udacity: https://t.me/techpsyche/633
ML Crash Course by Google
https://developers.google.com/machine-learning/crash-course
IBM Free Courses with Certification
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CISCO Free Certification Courses
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ENJOY LEARNING 👍👍
Follow this WhatsApp Channel for More Resources
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
1. Python
- learnpython.org
- t.me/pythonresourcestp
2. Java
- learnjavaonline.org
- t.me/javaresourcestp
3. C#
- learncs.org
- w3schools.com
4. JavaScript
- learnjavascript.online
- t.me/javascriptresourcestp
5. Rust
- rust-lang.org
- exercism.org
6. Go Programming
- go.dev
- learn-golang.org
7. Kotlin
- kotlinlang.org
- w3schools.com/KOTLIN
8. TypeScript
- Typescriptlang.org
- learntypescript.dev
9. SQL
- datasimplifier.com
- t.me/sqlresourcestp
10. R Programming
- w3schools.com/r/
- r-coder.com
ENJOY LEARNING 👍👍
3 FREE Courses by Google, Microsoft & LinkedIn
https://tinyurl.com/3w3xu4sh
7 Free Courses by Udacity: https://t.me/techpsyche/633
ML Crash Course by Google
https://developers.google.com/machine-learning/crash-course
IBM Free Courses with Certification
https://tinyurl.com/42nau8jx
CISCO Free Certification Courses
https://bit.ly/4i9Kc9Z
ENJOY LEARNING 👍👍
Follow this WhatsApp Channel for More Resources
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
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