AI Skills

🔰 PHP with MySQL: Build Amazing Streaming Service 🌟 4.2 - 69 votes 💰 Original Price: $27.99

📖 Build Fancy Streaming Service with Admin Panel in PHP MySQL Bootstrap and PDO

🔊 Taught By: Web Coding 📤 Download Full Course 📤 Download All Courses

📖 The Complete SQL Bootcamp: Go from Zero to Hero 🌟 4.7 - 223280 votes 💰 Original Price: $74.99

📖 You'll learn how to read and write complex queries to a database using one of the most in demand skills - PostgreSQL. These skills are also applicable to any other major SQL database, such as MySQL, Microsoft SQL Server, Amazon Redshift, Oracle, and much more. Learning SQL is one of the fastest ways to improve your career prospects as it is one of the most in demand tech skills! In this course you'll learn quickly and receive challenges and tests along the way to improve your understanding!

🔊 Taught By: Jose Portilla, Pierian Training 📤 Download Full Course 📤 Download All Courses

📖 Most important SQL commands

These key SQL commands are the basics you need to handle and organize data like a pro.

📖 30 days roadmap to learn Python for Data Analysis 😄👇 Days 1-5: Introduction to Python 1. Day 1: Install Python and a code editor (e.g., Anaconda, Jupyter Notebook). 2. Day 2-5: Learn Python basics (variables, data types, and basic operations). Days 6-10: Control Flow and Functions 6. Day 6-8: Study control flow (if statements, loops). 9. Day 9-10: Learn about functions and modules in Python. Days 11-15: Data Structures 11. Day 11-12: Explore lists, tuples, and dictionaries. 13. Day 13-15: Study sets and string manipulation. Days 16-20: Libraries for Data Analysis 16. Day 16-17: Get familiar with NumPy for numerical operations. 18. Day 18-19: Dive into Pandas for data manipulation. 20. Day 20: Basic data visualization with Matplotlib. Days 21-25: Data Cleaning and Analysis 21. Day 21-22: Data cleaning and preprocessing using Pandas. 23. Day 23-25: Exploratory data analysis (EDA) techniques. Days 26-30: Advanced Topics 26. Day 26-27: Introduction to data visualization with Seaborn. 27. Day 28-29: Introduction to machine learning with Scikit-Learn. 30. Day 30: Create a small data analysis project. Use platforms like Kaggle to find datasets for projects & GeekforGeeks to practice coding problems. ENJOY LEARNING 👍👍

🔗 Master AI (Artificial Intelligence) in 10 days 👇👇 Day 1: Introduction to AI - Start with an overview of what AI is and its various applications. - Read articles or watch videos explaining the basics of AI. Day 2-3: Machine Learning Fundamentals - Learn the basics of machine learning, including supervised and unsupervised learning. - Study concepts like data, features, labels, and algorithms. Day 4-5: Deep Learning - Dive into deep learning, understanding neural networks and their architecture. - Learn about popular deep learning frameworks like TensorFlow or PyTorch. Day 6: Natural Language Processing (NLP) - Explore the basics of NLP, including tokenization, sentiment analysis, and named entity recognition. Day 7: Computer Vision - Study computer vision, including image recognition, object detection, and convolutional neural networks. Day 8: AI Ethics and Bias - Explore the ethical considerations in AI and the issue of bias in AI algorithms. Day 9: AI Tools and Resources - Familiarize yourself with AI development tools and platforms. - Learn how to access and use AI datasets and APIs. Day 10: AI Project - Work on a small AI project. For example, build a basic chatbot, create an image classifier, or analyze a dataset using AI techniques. ENJOY LEARNING 👍👍

Top 9 machine learning algorithms

💰 Building The Machine Learning Model

🔅 Tweaking Custom Environment Rewards - Reinforcement Learning with Stable Baselines 3 (P.4)

Helping our reinforcement learning algorithm to learn better by tweaking the environment rewards.