List of 40+ Cheat Sheets
1. HTML & CSS :- htmlcheatsheet.com
2. JavaScript :- https://quickref.me/javascript
3. Jquery :- https://oscarotero.com/jquery/
4. Bootstrap 5 :- https://lnkd.in/dNZ6qdBh
5. Tailwind CSS :- https://lnkd.in/d_T5q5Tx
6. React :- https://t.me/javascriptresourcestp/460
7. Python :- https://t.me/pythonresourcestp/71
8. MongoDB :- https://lnkd.in/dBXxCQ43
9. SQL :- https://t.me/sqlresourcestp/8
10. Nodejs :- https://lnkd.in/dwry8BKH
11. Expressjs :- https://quickref.me/express
12. Django :- https://lnkd.in/dYWQKZnT
13. PHP :- https://quickref.me/php
14. Google Dork :- https://lnkd.in/dKej3-42
15. Linux :- https://lnkd.in/dCgH_qUq
16. Git :- https://t.me/techpsyche/131
17. VSCode :- https://quickref.me/vscode
18. Deep Learning :- https://t.me/mlresourcestp/5
19. Data Structures and Algorithms :- https://lnkd.in/d75ijyr3
20. DSA Practice :- https://lnkd.in/dDc6SaR8
21. Data Science :- https://lnkd.in/dHaxPYYA
22. Flask :- https://lnkd.in/dkUyWHqR
23. CCNA :- https://lnkd.in/dE_yD6ny
24. Cloud Computing :- https://lnkd.in/d9vggegr
25. Machine Learning :- https://t.me/mlresourcestp/9
26. Windows Command :- https://lnkd.in/dAMeCywP
27. Computer Basics :- https://lnkd.in/d9yaNaWN
28. MySQL :- https://lnkd.in/d7iJjSpQ
29. PostgreSQL :- https://lnkd.in/dDHQkk5f
30. MSExcel :- https://t.me/dataanalysisresourcestp/92
31. MSWord :- https://lnkd.in/dAX4FGkR
32. Java :- https://lnkd.in/dRe98iSB
33. Cryptography :- https://lnkd.in/dYvRHAH9
34. C++ :- https://lnkd.in/d4GjE2kd
35. C :- https://lnkd.in/diuHU72d
36. Resume Creation :- https://t.me/techpsyche/495
37. ChatGPT :- https://t.me/airesourcestp/73
38. Docker :- https://lnkd.in/dNVJxYNa
39. R Programming :- datacamp.com/cheat-sheet/getting-started-r
40. AngularJS :- https://v17.angular.io/guide/cheatsheet
Find More Tips & Resources Here:
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
1. HTML & CSS :- htmlcheatsheet.com
2. JavaScript :- https://quickref.me/javascript
3. Jquery :- https://oscarotero.com/jquery/
4. Bootstrap 5 :- https://lnkd.in/dNZ6qdBh
5. Tailwind CSS :- https://lnkd.in/d_T5q5Tx
6. React :- https://t.me/javascriptresourcestp/460
7. Python :- https://t.me/pythonresourcestp/71
8. MongoDB :- https://lnkd.in/dBXxCQ43
9. SQL :- https://t.me/sqlresourcestp/8
10. Nodejs :- https://lnkd.in/dwry8BKH
11. Expressjs :- https://quickref.me/express
12. Django :- https://lnkd.in/dYWQKZnT
13. PHP :- https://quickref.me/php
14. Google Dork :- https://lnkd.in/dKej3-42
15. Linux :- https://lnkd.in/dCgH_qUq
16. Git :- https://t.me/techpsyche/131
17. VSCode :- https://quickref.me/vscode
18. Deep Learning :- https://t.me/mlresourcestp/5
19. Data Structures and Algorithms :- https://lnkd.in/d75ijyr3
20. DSA Practice :- https://lnkd.in/dDc6SaR8
21. Data Science :- https://lnkd.in/dHaxPYYA
22. Flask :- https://lnkd.in/dkUyWHqR
23. CCNA :- https://lnkd.in/dE_yD6ny
24. Cloud Computing :- https://lnkd.in/d9vggegr
25. Machine Learning :- https://t.me/mlresourcestp/9
26. Windows Command :- https://lnkd.in/dAMeCywP
27. Computer Basics :- https://lnkd.in/d9yaNaWN
28. MySQL :- https://lnkd.in/d7iJjSpQ
29. PostgreSQL :- https://lnkd.in/dDHQkk5f
30. MSExcel :- https://t.me/dataanalysisresourcestp/92
31. MSWord :- https://lnkd.in/dAX4FGkR
32. Java :- https://lnkd.in/dRe98iSB
33. Cryptography :- https://lnkd.in/dYvRHAH9
34. C++ :- https://lnkd.in/d4GjE2kd
35. C :- https://lnkd.in/diuHU72d
36. Resume Creation :- https://t.me/techpsyche/495
37. ChatGPT :- https://t.me/airesourcestp/73
38. Docker :- https://lnkd.in/dNVJxYNa
39. R Programming :- datacamp.com/cheat-sheet/getting-started-r
40. AngularJS :- https://v17.angular.io/guide/cheatsheet
Find More Tips & Resources Here:
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
Forwarded from SQL Resources TP
Many people charge too much to teach SQL, but my mission is to break down barriers. I have shared complete learning series to learn SQL from scratch.
Here are the links to the SQL series
Complete SQL Topics for Data Analyst: https://t.me/sqlresourcestp/83
Part-1: https://t.me/sqlresourcestp/58
Part-2: https://t.me/sqlresourcestp/59
Part-3: https://t.me/sqlresourcestp/60
Part-4: https://t.me/sqlresourcestp/61
Part-5: https://t.me/sqlresourcestp/62
Part-6: https://t.me/sqlresourcestp/63
Part-7: https://t.me/sqlresourcestp/64
Part-8: https://t.me/sqlresourcestp/65
Part-9: https://t.me/sqlresourcestp/66
Part-10: https://t.me/sqlresourcestp/67
Part-11: https://t.me/sqlresourcestp/68
Part-12: https://t.me/sqlresourcestp/71
Part-13: https://t.me/sqlresourcestp/72
Part-14: https://t.me/sqlresourcestp/73
Part-15: https://t.me/sqlresourcestp/74
Part-16: https://t.me/sqlresourcestp/75
Part-17: https://t.me/sqlresourcestp/76
Part-18: https://t.me/sqlresourcestp/77
Part-19: https://t.me/sqlresourcestp/80
Part-20: https://t.me/sqlresourcestp/81
Thanks to all who support our channel and share the content with proper credits. You guys are really amazing.
Complete Excel Topics for Data Analysts: https://t.me/dataanalysisresourcestp/93
Here you can find SQL Interview Resources๐
https://t.me/sqlresourcestp/40
Hope it helps :)
Follow this WhatsApp Channel for More Resources:
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
Here are the links to the SQL series
Complete SQL Topics for Data Analyst: https://t.me/sqlresourcestp/83
Part-1: https://t.me/sqlresourcestp/58
Part-2: https://t.me/sqlresourcestp/59
Part-3: https://t.me/sqlresourcestp/60
Part-4: https://t.me/sqlresourcestp/61
Part-5: https://t.me/sqlresourcestp/62
Part-6: https://t.me/sqlresourcestp/63
Part-7: https://t.me/sqlresourcestp/64
Part-8: https://t.me/sqlresourcestp/65
Part-9: https://t.me/sqlresourcestp/66
Part-10: https://t.me/sqlresourcestp/67
Part-11: https://t.me/sqlresourcestp/68
Part-12: https://t.me/sqlresourcestp/71
Part-13: https://t.me/sqlresourcestp/72
Part-14: https://t.me/sqlresourcestp/73
Part-15: https://t.me/sqlresourcestp/74
Part-16: https://t.me/sqlresourcestp/75
Part-17: https://t.me/sqlresourcestp/76
Part-18: https://t.me/sqlresourcestp/77
Part-19: https://t.me/sqlresourcestp/80
Part-20: https://t.me/sqlresourcestp/81
Thanks to all who support our channel and share the content with proper credits. You guys are really amazing.
Complete Excel Topics for Data Analysts: https://t.me/dataanalysisresourcestp/93
Here you can find SQL Interview Resources๐
https://t.me/sqlresourcestp/40
Hope it helps :)
Follow this WhatsApp Channel for More Resources:
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
Forwarded from Web Development Resources TP
20 Backend Project Ideas๐ฅ
๐นAPI for a Task Management System
๐นTo-Do List API
๐นBlog Platform
๐นMarkdown Note-taking App
๐นOnline Code Compiler API
๐นE-commerce API
๐นURL Shortening Service
๐นChat Application Backend
๐นWeb Scraper CLI
๐นOnline Bookstore
๐นSocial Media API
๐นMusic Streaming App
๐นFitness Workout Tracker
๐นAuthentication and Authorization Service
๐นFile Upload and Management System
๐นRecipe Sharing Platform
๐นEvent Booking System
๐นExpense Tracker API
๐นWeather Forecast Service
๐นOnline Food Ordering System
FullStack Project Ideas: https://t.me/webdevresourcestp/31
Python Project Ideas: https://t.me/pythonresourcestp/74
Web Development Project Ideas: https://t.me/webdevresourcestp/40
Make sure to scroll through the above messages ๐ you will definitely find more interesting things ๐ค
Follow this WhatsApp Channel for More Resources
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
๐นAPI for a Task Management System
๐นTo-Do List API
๐นBlog Platform
๐นMarkdown Note-taking App
๐นOnline Code Compiler API
๐นE-commerce API
๐นURL Shortening Service
๐นChat Application Backend
๐นWeb Scraper CLI
๐นOnline Bookstore
๐นSocial Media API
๐นMusic Streaming App
๐นFitness Workout Tracker
๐นAuthentication and Authorization Service
๐นFile Upload and Management System
๐นRecipe Sharing Platform
๐นEvent Booking System
๐นExpense Tracker API
๐นWeather Forecast Service
๐นOnline Food Ordering System
FullStack Project Ideas: https://t.me/webdevresourcestp/31
Python Project Ideas: https://t.me/pythonresourcestp/74
Web Development Project Ideas: https://t.me/webdevresourcestp/40
Make sure to scroll through the above messages ๐ you will definitely find more interesting things ๐ค
Follow this WhatsApp Channel for More Resources
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
โค1
THANK YOU !!!
Thank you being Part of this Channel.
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Start learning today and land your dream job in analytics!
๐๐ถ๐ป๐ธ๐ :-
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Enroll For FREE & Get Certified ๐
Useful Cheatsheets for Programmers๐๐
Data Science Cheatsheet
https://github.com/aaronwangy/Data-Science-Cheatsheet
SQL Cheatsheet
https://t.me/sqlresourcestp/90
https://www.sqltutorial.org/wp-content/uploads/2016/04/SQL-cheat-sheet.pdf
Java Programming Cheatsheet
https://introcs.cs.princeton.edu/java/11cheatsheet/
Data Analytics Cheatsheets
https://dataanalytics.beehiiv.com/p/data
Python Cheat sheet
https://t.me/pythonresourcestp/42
GIT Cheatsheet
https://t.me/techpsyche/131
Machine Learning Cheatsheet
https://t.me/mlresourcestp/9
HTML Cheatsheet
https://web.stanford.edu/group/csp/cs21/htmlcheatsheet.pdf
jQuery Cheatsheet
https://t.me/javascriptresourcestp/462
Like for more โค๏ธ
Join for more free resources
https://t.me/techpsyche
ENJOY LEARNING๐๐
More Resources on this WhatsApp Channel
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
Data Science Cheatsheet
https://github.com/aaronwangy/Data-Science-Cheatsheet
SQL Cheatsheet
https://t.me/sqlresourcestp/90
https://www.sqltutorial.org/wp-content/uploads/2016/04/SQL-cheat-sheet.pdf
Java Programming Cheatsheet
https://introcs.cs.princeton.edu/java/11cheatsheet/
Data Analytics Cheatsheets
https://dataanalytics.beehiiv.com/p/data
Python Cheat sheet
https://t.me/pythonresourcestp/42
GIT Cheatsheet
https://t.me/techpsyche/131
Machine Learning Cheatsheet
https://t.me/mlresourcestp/9
HTML Cheatsheet
https://web.stanford.edu/group/csp/cs21/htmlcheatsheet.pdf
jQuery Cheatsheet
https://t.me/javascriptresourcestp/462
Like for more โค๏ธ
Join for more free resources
https://t.me/techpsyche
ENJOY LEARNING๐๐
More Resources on this WhatsApp Channel
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
Forwarded from Artificial Intelligence Resources TP . AI Tools . AI Updates
10 free tools to become top level creator.
1. Idea - Google
2. Research - ChatGPT
3. Script - Notion
4. Recoding - Audacity
5. Thumbnail - Canva
6. Editing - Davinci resolve
7. Stock Video - Mixkit
8. Captions - Clipchamp
9. Music & effect - YT Library
10. Scheduling - Buffer
13 AI Tools to 10X your Productivity: https://t.me/airesourcestp/94
10 AI Tools to save you Hours: https://t.me/airesourcestp/102
40 Content Creation Tools: https://t.me/airesourcestp/109
ENJOY LEARNING ๐๐
More Resources Here:
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
1. Idea - Google
2. Research - ChatGPT
3. Script - Notion
4. Recoding - Audacity
5. Thumbnail - Canva
6. Editing - Davinci resolve
7. Stock Video - Mixkit
8. Captions - Clipchamp
9. Music & effect - YT Library
10. Scheduling - Buffer
13 AI Tools to 10X your Productivity: https://t.me/airesourcestp/94
10 AI Tools to save you Hours: https://t.me/airesourcestp/102
40 Content Creation Tools: https://t.me/airesourcestp/109
ENJOY LEARNING ๐๐
More Resources Here:
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
๐1
2025 % of all code written by AI = 50%
2026 % of all code written by AI = 100%
This was Anthropic CEO's prediction
I say
Accurate Prediction
2025 % of all code written by AI = 50%
2026 % of all code written by AI = 100%
2027 % of all code written by AI = 75%
2028 a lot of very very expensive senior developers make bank undoing all the garbage written in 2026
2026 % of all code written by AI = 100%
This was Anthropic CEO's prediction
I say
Accurate Prediction
2025 % of all code written by AI = 50%
2026 % of all code written by AI = 100%
2027 % of all code written by AI = 75%
2028 a lot of very very expensive senior developers make bank undoing all the garbage written in 2026
๐ก Here are 5 passive income ideas for developers๐จ๐ปโ๐ป -
1. Build and Sell Apps or Plugins ๐ ๐ฑ
Create a simple app, browser extension, or WordPress plugin. Publish it, set a price, and let the downloads roll in! ๐ต
2. Launch an Online Course ๐๐ป
Share your coding wisdom! Record tutorials on platforms like Udemy or Gumroad, and earn every time someone enrolls. ๐โจ
3. Develop SaaS Products โ๏ธ๐
Solve a niche problem with a subscription-based software service. Think task trackers, productivity tools, or analytics dashboards! ๐ก๐ฐ
4. Write a Tech Ebook ๐๐จโ๐ป
Document your expertise in a programming language or framework. Publish it on Amazon or Leanpub and watch the royalties stack up. ๐๐ธ
5. Create a YouTube Channel ๐น๐ป
Share coding tutorials, dev tips, or even live coding sessions. Once you get enough views and subscribers, YouTube ads, sponsorships, and memberships can bring in steady income! ๐ฌ๐ฐ
1. Build and Sell Apps or Plugins ๐ ๐ฑ
Create a simple app, browser extension, or WordPress plugin. Publish it, set a price, and let the downloads roll in! ๐ต
2. Launch an Online Course ๐๐ป
Share your coding wisdom! Record tutorials on platforms like Udemy or Gumroad, and earn every time someone enrolls. ๐โจ
3. Develop SaaS Products โ๏ธ๐
Solve a niche problem with a subscription-based software service. Think task trackers, productivity tools, or analytics dashboards! ๐ก๐ฐ
4. Write a Tech Ebook ๐๐จโ๐ป
Document your expertise in a programming language or framework. Publish it on Amazon or Leanpub and watch the royalties stack up. ๐๐ธ
5. Create a YouTube Channel ๐น๐ป
Share coding tutorials, dev tips, or even live coding sessions. Once you get enough views and subscribers, YouTube ads, sponsorships, and memberships can bring in steady income! ๐ฌ๐ฐ
Forwarded from Free Courses: Google | Microsoft | Udemy | Coursera | IBM | NVIDIA | LinkedIn Learning | MIT | Udemy Coupons & PDF Books
20th ๐ฅ March 2025 Free Udemy Coupons New Coupons Added
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#02 Java And C++ Complete Course for Java And C++ Beginners
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#04 Java Programming - Master Java Basics
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#05 Java And C++ And PHP Crash Course All in One For Beginners
https://techurl.in/WcbgH
#06 Java Programming Masterclass - Beginner to Master
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โโโโโโโโโโโโโโโโโโโโโ
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**Do share in your groups.โจ**
KenyaTrends.co.ke
Kenya Trends - Jobs | Opportunities | Free Resources
Sharing free learning resources, jobs & opportunities.
๐1
Microsoft ๐ฃ๐๐ฆ๐ฝ๐ฎ๐ฟ๐ธ interview questions for Data Engineer 2024.
1. How would you optimize a PySpark DataFrame operation that involves multiple transformations and is running too slowly on a large dataset?
2. Given a large dataset that doesnโt fit in memory, how would you convert a Pandas DataFrame to a PySpark DataFrame for scalable processing?
3. You have a large dataset with a highly skewed distribution. How would you handle data skewness in PySpark to ensure that your jobs do not fail or take too long to execute?
4. How do you optimize data partitioning in PySpark? When and how would you use repartition() and coalesce()?
5. Write a PySpark code snippet to calculate the moving average of a column for each partition of data, using window functions.
6. How would you handle null values in a PySpark DataFrame when different columns require different strategies (e.g., dropping, replacing, or imputing)?
7. When would you use a broadcast join in PySpark? Provide an example where broadcasting improves performance and explain the limitations.
8. When should you use UDFs instead of built-in PySpark functions, and how do you ensure UDFs are optimized for performance?
PySpark Concepts: https://t.me/datascienceresourcestp/63
Data Engineering Course: https://udemy.com/course/learn-data-engineering/
KAFKA Interview Questions: https://t.me/datascienceresourcestp/80
All the best ๐๐
Join Our WhatsApp Channel:
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
1. How would you optimize a PySpark DataFrame operation that involves multiple transformations and is running too slowly on a large dataset?
2. Given a large dataset that doesnโt fit in memory, how would you convert a Pandas DataFrame to a PySpark DataFrame for scalable processing?
3. You have a large dataset with a highly skewed distribution. How would you handle data skewness in PySpark to ensure that your jobs do not fail or take too long to execute?
4. How do you optimize data partitioning in PySpark? When and how would you use repartition() and coalesce()?
5. Write a PySpark code snippet to calculate the moving average of a column for each partition of data, using window functions.
6. How would you handle null values in a PySpark DataFrame when different columns require different strategies (e.g., dropping, replacing, or imputing)?
7. When would you use a broadcast join in PySpark? Provide an example where broadcasting improves performance and explain the limitations.
8. When should you use UDFs instead of built-in PySpark functions, and how do you ensure UDFs are optimized for performance?
PySpark Concepts: https://t.me/datascienceresourcestp/63
Data Engineering Course: https://udemy.com/course/learn-data-engineering/
KAFKA Interview Questions: https://t.me/datascienceresourcestp/80
All the best ๐๐
Join Our WhatsApp Channel:
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
Complete Data Science Roadmap ๐๐
1. Introduction to Data Science
- Overview and Importance
- Data Science Lifecycle
- Key Roles (Data Scientist, Analyst, Engineer)
2. Mathematics and Statistics
- Probability and Distributions
- Descriptive/Inferential Statistics
- Hypothesis Testing
- Linear Algebra and Calculus Basics
3. Programming Languages
- Python: NumPy, Pandas, Matplotlib
- R: dplyr, ggplot2
- SQL: Joins, Aggregations, CRUD
4. Data Collection & Preprocessing
- Data Cleaning and Wrangling
- Handling Missing Data
- Feature Engineering
5. Exploratory Data Analysis (EDA)
- Summary Statistics
- Data Visualization (Histograms, Box Plots, Correlation)
6. Machine Learning
- Supervised (Linear/Logistic Regression, Decision Trees)
- Unsupervised (K-Means, PCA)
- Model Selection and Cross-Validation
7. Advanced Machine Learning
- SVM, Random Forests, Boosting
- Neural Networks Basics
8. Deep Learning
- Neural Networks Architecture
- CNNs for Image Data
- RNNs for Sequential Data
9. Natural Language Processing (NLP)
- Text Preprocessing
- Sentiment Analysis
- Word Embeddings (Word2Vec)
10. Data Visualization & Storytelling
- Dashboards (Tableau, Power BI)
- Telling Stories with Data
11. Model Deployment
- Deploy with Flask or Django
- Monitoring and Retraining Models
12. Big Data & Cloud
- Introduction to Hadoop, Spark
- Cloud Tools (AWS, Google Cloud)
13. Data Engineering Basics
- ETL Pipelines
- Data Warehousing (Redshift, BigQuery)
14. Ethics in Data Science
- Ethical Data Usage
- Bias in AI Models
15. Tools for Data Science
- Jupyter, Git, Docker
16. Career Path & Certifications
- Building a Data Science Portfolio
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 ๐๐
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 โค๏ธ
ENJOY LEARNING๐๐
Join Our WhatsApp Channel:
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
1. Introduction to Data Science
- Overview and Importance
- Data Science Lifecycle
- Key Roles (Data Scientist, Analyst, Engineer)
2. Mathematics and Statistics
- Probability and Distributions
- Descriptive/Inferential Statistics
- Hypothesis Testing
- Linear Algebra and Calculus Basics
3. Programming Languages
- Python: NumPy, Pandas, Matplotlib
- R: dplyr, ggplot2
- SQL: Joins, Aggregations, CRUD
4. Data Collection & Preprocessing
- Data Cleaning and Wrangling
- Handling Missing Data
- Feature Engineering
5. Exploratory Data Analysis (EDA)
- Summary Statistics
- Data Visualization (Histograms, Box Plots, Correlation)
6. Machine Learning
- Supervised (Linear/Logistic Regression, Decision Trees)
- Unsupervised (K-Means, PCA)
- Model Selection and Cross-Validation
7. Advanced Machine Learning
- SVM, Random Forests, Boosting
- Neural Networks Basics
8. Deep Learning
- Neural Networks Architecture
- CNNs for Image Data
- RNNs for Sequential Data
9. Natural Language Processing (NLP)
- Text Preprocessing
- Sentiment Analysis
- Word Embeddings (Word2Vec)
10. Data Visualization & Storytelling
- Dashboards (Tableau, Power BI)
- Telling Stories with Data
11. Model Deployment
- Deploy with Flask or Django
- Monitoring and Retraining Models
12. Big Data & Cloud
- Introduction to Hadoop, Spark
- Cloud Tools (AWS, Google Cloud)
13. Data Engineering Basics
- ETL Pipelines
- Data Warehousing (Redshift, BigQuery)
14. Ethics in Data Science
- Ethical Data Usage
- Bias in AI Models
15. Tools for Data Science
- Jupyter, Git, Docker
16. Career Path & Certifications
- Building a Data Science Portfolio
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 ๐๐
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 โค๏ธ
ENJOY LEARNING๐๐
Join Our WhatsApp Channel:
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R