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.me/pythonresourcestp/100
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.me/dataanalysisresourcestp
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.me/sqlresourcestp
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://tinyurl.com/2b76wzud
8. Machine Learning Basics: Familiarize yourself with basic machine learning concepts. This knowledge can be beneficial for advanced analytics tasks.
ML Basics: https://t.me/mlresourcestp/72
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.me/dataanalysisresourcestp/33
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.me/techpsyche
12. Effective Communication: Develop strong communication skills. Being able to convey your findings and insights in a clear and understandable manner is crucial.
Data Analysis & Visualization Free Course: https://tinyurl.com/2b76wzud
Tableau Learning Plan
https://t.me/dataanalysisresourcestp/84
7 Free Data Analytics Courses👇👇
https://tinyurl.com/326exaw7
Data Analyst Checklist
https://t.me/dataanalysisresourcestp/99
Hope it helps :)
Share our channel link with your friends:
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
1. Learn the Basics: Begin with understanding the fundamental concepts of statistics, mathematics, and programming languages like Python or R.
Free Resources: https://t.me/pythonresourcestp/100
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.me/dataanalysisresourcestp
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.me/sqlresourcestp
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://tinyurl.com/2b76wzud
8. Machine Learning Basics: Familiarize yourself with basic machine learning concepts. This knowledge can be beneficial for advanced analytics tasks.
ML Basics: https://t.me/mlresourcestp/72
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.me/dataanalysisresourcestp/33
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.me/techpsyche
12. Effective Communication: Develop strong communication skills. Being able to convey your findings and insights in a clear and understandable manner is crucial.
Data Analysis & Visualization Free Course: https://tinyurl.com/2b76wzud
Tableau Learning Plan
https://t.me/dataanalysisresourcestp/84
7 Free Data Analytics Courses👇👇
https://tinyurl.com/326exaw7
Data Analyst Checklist
https://t.me/dataanalysisresourcestp/99
Hope it helps :)
Share our channel link with your friends:
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
Forwarded from Crypto Stract | Web 3, Finance, Business, Blockchain, Crypto, Growth, Stock Market, Money
✔️ Last week's crypto market highlights
⚫️ Blum co-founder Smerkis arrested in Moscow on fraud charges
⚫️ Russia drafts bill to seize digital currency in crimes
⚫️ Strategy acquires 7,390 BTC for $764.9m
⚫️ Argentina shuts down LIBRA memecoin investigation unit
⚫️ Societe Generale to launch USD-pegged stablecoin on Ethereum
⚫️ South Korea lifts crypto investment ban in June
⚫️ Bitcoin hits new all-time high surpassing $110,000
⚫️ Kraken to offer tokenized stocks and ETFs
⚫️ Cetus loses $220m in smart contract exploit
⚫️ Trump recommends 50% tariff on EU goods
⚡️ t.me/cryptostract
⚫️ Blum co-founder Smerkis arrested in Moscow on fraud charges
⚫️ Russia drafts bill to seize digital currency in crimes
⚫️ Strategy acquires 7,390 BTC for $764.9m
⚫️ Argentina shuts down LIBRA memecoin investigation unit
⚫️ Societe Generale to launch USD-pegged stablecoin on Ethereum
⚫️ South Korea lifts crypto investment ban in June
⚫️ Bitcoin hits new all-time high surpassing $110,000
⚫️ Kraken to offer tokenized stocks and ETFs
⚫️ Cetus loses $220m in smart contract exploit
⚫️ Trump recommends 50% tariff on EU goods
⚡️ t.me/cryptostract
❤1
Remote Data Analyst Job - Binance Accelerator Program
Who may apply?
- Current university students and recent graduates
Apply Here:
https://kenyatrends.co.ke/ri5q
Global Tech Jobs Here👇
https://t.me/techpsyche
SHARE WITH YOUR FRIENDS🥳🥳
Who may apply?
- Current university students and recent graduates
Apply Here:
https://kenyatrends.co.ke/ri5q
Global Tech Jobs Here👇
https://t.me/techpsyche
SHARE WITH YOUR FRIENDS🥳🥳
Forwarded from Artificial Intelligence Resources TP . AI Tools . AI Updates
LLM's for the Messy Middle tasks.
Forwarded from Crypto Stract | Web 3, Finance, Business, Blockchain, Crypto, Growth, Stock Market, Money
This is a problem when people make 6 figures.
They ape into supercars and fancy stuff.
When they could have aped into investments and become decamillionaires.
Super short sighted.
⚡️ t.me/cryptostract
They ape into supercars and fancy stuff.
When they could have aped into investments and become decamillionaires.
Super short sighted.
⚡️ t.me/cryptostract
📊 Next-level charts in seconds
Tired of boring reports and lifeless slides? We’ve got you. Here’s a roundup of tools to turn your data into clear, scroll-stopping visuals..fast.
• Datawrapper: Perfect for quick charts right in your browser. Great when you’ve got a meeting in 10 minutes and need to make the numbers look smart. Bonus: weekly inspo from the best visualizations.
• Flourish: Want your charts to move? This one’s for making interactive, animated graphics that actually hold attention. Even boring stats start to look cool.
• RAWGraphs: An open-source tool for weird and wonderful custom charts. You can map your data into just about any shape. Yes, even a capybara.
💼 Save this for your next report. (https://t.me/dataanalysisresourcestp/181)
More Data Visualization Resources Here:
https://t.me/dataanalysisresourcestp
Tired of boring reports and lifeless slides? We’ve got you. Here’s a roundup of tools to turn your data into clear, scroll-stopping visuals..fast.
• Datawrapper: Perfect for quick charts right in your browser. Great when you’ve got a meeting in 10 minutes and need to make the numbers look smart. Bonus: weekly inspo from the best visualizations.
• Flourish: Want your charts to move? This one’s for making interactive, animated graphics that actually hold attention. Even boring stats start to look cool.
• RAWGraphs: An open-source tool for weird and wonderful custom charts. You can map your data into just about any shape. Yes, even a capybara.
💼 Save this for your next report. (https://t.me/dataanalysisresourcestp/181)
More Data Visualization Resources Here:
https://t.me/dataanalysisresourcestp
Complete Roadmap to land a Data Scientist job in 2025
Phase 1: Build Foundations (3-6 months)
1. Learn Python programming basics
2. Understand statistics and mathematics concepts (linear algebra, calculus, probability)
3. Familiarize yourself with data visualization tools (Matplotlib, Seaborn)
Phase 2: Data Science Skills (6-9 months)
1. Master machine learning algorithms (scikit-learn, TensorFlow)
2. Learn data manipulation frameworks (Pandas, NumPy)
3. Study data visualization libraries (Plotly, Bokeh)
4. Understand database management systems (SQL, NoSQL)
Phase 3: Practice and Projects (3-6 months)
1. Work on personal projects (Kaggle competitions, datasets)
2. Participate in data science communities (GitHub, Reddit)
3. Build a portfolio showcasing skills
Phase 4: Job Preparation (1-3 months)
1. Update resume and online profiles (LinkedIn)
2. Practice whiteboarding and coding interviews
3. Prepare answers for common data science questions
Best Resources to learn Data Science 👇👇
Python Tutorial (http://pythontutorial.net/)
Interview Process for Data Science Role at Amazon (https://t.me/datascienceresourcestp/104)
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)
Python Interview Resources (https://t.me/pythonresourcestp/40)
Like for more ❤️
ENJOY LEARNING👍👍
Follow This WhatsApp Channel for More Resources:
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
Phase 1: Build Foundations (3-6 months)
1. Learn Python programming basics
2. Understand statistics and mathematics concepts (linear algebra, calculus, probability)
3. Familiarize yourself with data visualization tools (Matplotlib, Seaborn)
Phase 2: Data Science Skills (6-9 months)
1. Master machine learning algorithms (scikit-learn, TensorFlow)
2. Learn data manipulation frameworks (Pandas, NumPy)
3. Study data visualization libraries (Plotly, Bokeh)
4. Understand database management systems (SQL, NoSQL)
Phase 3: Practice and Projects (3-6 months)
1. Work on personal projects (Kaggle competitions, datasets)
2. Participate in data science communities (GitHub, Reddit)
3. Build a portfolio showcasing skills
Phase 4: Job Preparation (1-3 months)
1. Update resume and online profiles (LinkedIn)
2. Practice whiteboarding and coding interviews
3. Prepare answers for common data science questions
Best Resources to learn Data Science 👇👇
Python Tutorial (http://pythontutorial.net/)
Interview Process for Data Science Role at Amazon (https://t.me/datascienceresourcestp/104)
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)
Python Interview Resources (https://t.me/pythonresourcestp/40)
Like for more ❤️
ENJOY LEARNING👍👍
Follow This WhatsApp Channel for More Resources:
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
🇫🇮 🏴 Man used AI to make child abuse images
A Scottish court has sentenced telecoms worker Risto Bergman, 42, to an 18-month Community Payback Order for generating child sex abuse images using artificial intelligence. Originally from Finland, Bergman used a publicly available AI app and explicit search terms to create highly realistic images of young girls being abused. Prosecutors revealed that the app relied on a digital archive of real child abuse material shared by pedophiles online.
Some of the AI-generated images were classified as Category A, the UK’s most extreme level of abuse content. The material was discovered on a storage unit in Bergman’s former home in Paisley. Bergman pleaded guilty to the charges and was added to the sex offenders’ register, but avoided jail time. Prosecutor David Bernard emphasised that this was not a victimless crime, as each AI image depicted real children who had been abused to create the source material.
🔆 t.me/techpsyche
A Scottish court has sentenced telecoms worker Risto Bergman, 42, to an 18-month Community Payback Order for generating child sex abuse images using artificial intelligence. Originally from Finland, Bergman used a publicly available AI app and explicit search terms to create highly realistic images of young girls being abused. Prosecutors revealed that the app relied on a digital archive of real child abuse material shared by pedophiles online.
Some of the AI-generated images were classified as Category A, the UK’s most extreme level of abuse content. The material was discovered on a storage unit in Bergman’s former home in Paisley. Bergman pleaded guilty to the charges and was added to the sex offenders’ register, but avoided jail time. Prosecutor David Bernard emphasised that this was not a victimless crime, as each AI image depicted real children who had been abused to create the source material.
🔆 t.me/techpsyche
Forwarded from Mobile Dev Resources . Android . iOS . Flutter . Kotlin . Swift . Java . React Native
🎬 Top 5 Must-Subscribe YouTube Channels for Flutter Developers 🚀
1️⃣ The Net Ninja – Clear and concise Flutter tutorials, from beginner to advanced. Perfect for mastering the basics! 👨💻
2️⃣ Reso Coder – Deep dives into Flutter architecture, best practices, and clean code techniques. 🏗
3️⃣ Flutter (Official) – Stay updated with official tutorials, events, and Flutter releases straight from the source! 📢
4️⃣ CodeWithChris – Beginner-friendly tutorials with real-world Flutter app projects. Great for hands-on learning! 📱
5️⃣ Johannes Milke – Short and practical Flutter tips, covering widgets, packages, and UI design tricks. 💡
💥 Pro Tip: Watch and code along to speed up your Flutter skills! 🚀
Boost Your Flutter App Performance: https://t.me/mobiledevresourcestp/101
#flutter
1️⃣ The Net Ninja – Clear and concise Flutter tutorials, from beginner to advanced. Perfect for mastering the basics! 👨💻
2️⃣ Reso Coder – Deep dives into Flutter architecture, best practices, and clean code techniques. 🏗
3️⃣ Flutter (Official) – Stay updated with official tutorials, events, and Flutter releases straight from the source! 📢
4️⃣ CodeWithChris – Beginner-friendly tutorials with real-world Flutter app projects. Great for hands-on learning! 📱
5️⃣ Johannes Milke – Short and practical Flutter tips, covering widgets, packages, and UI design tricks. 💡
💥 Pro Tip: Watch and code along to speed up your Flutter skills! 🚀
Boost Your Flutter App Performance: https://t.me/mobiledevresourcestp/101
#flutter
Harvard CS50 – Free Computer Science Course (2023 Edition)
Here are the lectures included in this course:
Lecture 0 - Scratch
Lecture 1 - C
Lecture 2 - Arrays
Lecture 3 - Algorithms
Lecture 4 - Memory
Lecture 5 - Data Structures
Lecture 6 - Python
Lecture 7 - SQL
Lecture 8 - HTML, CSS, JavaScript
Lecture 9 - Flask
Lecture 10 - Emoji
Cybersecurity
Link: https://www.freecodecamp.org/news/harvard-university-cs50-computer-science-course-2023/
CS50 from Harvard
http://cs50.harvard.edu/x/2023/certificate/
NVIDIA FREE AI Certification Courses
https://t.me/techpsyche/617
IBM Free Certification Courses
https://tinyurl.com/42nau8jx
More Resources Here
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
Here are the lectures included in this course:
Lecture 0 - Scratch
Lecture 1 - C
Lecture 2 - Arrays
Lecture 3 - Algorithms
Lecture 4 - Memory
Lecture 5 - Data Structures
Lecture 6 - Python
Lecture 7 - SQL
Lecture 8 - HTML, CSS, JavaScript
Lecture 9 - Flask
Lecture 10 - Emoji
Cybersecurity
Link: https://www.freecodecamp.org/news/harvard-university-cs50-computer-science-course-2023/
CS50 from Harvard
http://cs50.harvard.edu/x/2023/certificate/
NVIDIA FREE AI Certification Courses
https://t.me/techpsyche/617
IBM Free Certification Courses
https://tinyurl.com/42nau8jx
More Resources Here
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
Forwarded from Artificial Intelligence Resources TP . AI Tools . AI Updates
Ai agents vs agentic AI.
INDIA📌Lexmark is hiring for Software Developer
Experience: 0 - 2 year's
Expected Salary: 8-16 LPA
Apply here: https://lexmark.wd1.myworkdayjobs.com/Lexmark/job/Lexmark-International-India/Software-Developer_R2840
WhatsApp Channel👇
https://whatsapp.com/channel/0029VbAqbkw6hENvEJZLl22d
Telegram Channel👇
https://t.me/jobsourceglobal
Forwarded from Machine Learning Resources TP
7 Baby steps to start with Machine Learning:
1. Start with Python
2. Learn to use Google Colab
3. Take a Pandas tutorial
4. Then a Seaborn tutorial
5. Decision Trees are a good first algorithm
6. Finish Kaggle's "Intro to Machine Learning"
7. Solve the Titanic challenge
ML Resources: t.me/mlresourcestp
1. Start with Python
2. Learn to use Google Colab
3. Take a Pandas tutorial
4. Then a Seaborn tutorial
5. Decision Trees are a good first algorithm
6. Finish Kaggle's "Intro to Machine Learning"
7. Solve the Titanic challenge
ML Resources: t.me/mlresourcestp
👍1