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New learning resources
5 Tool Design Secrets That AI Agents Actually Love
I’ve got a truth bomb for you: in today’s fast-moving world of AI, just adding more tools isn’t enough. We’re heading toward a future where AI agents — especially those powerful Large Language Models ...
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Working with Python Polars: DataFrames, Grouping, Aggregation, and the Lazy API
Polars is a high-performance data frame library designed to provide fast and efficient data processing capabilities. What you’ll learn in the full course: \- Why Polars is performant and intention gra...
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Building Advanced RAG Pipelines with Neo4j and LangChain: A Complete Guide to Knowledge…
Retrieval-Augmented Generation (RAG) has quickly become the go-to architecture for making Large Language Models (LLMs) useful in production. Instead of relying solely on the LLM’s internal memory, RAG...
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Learn Python
▶️ Basic Functions
Syntax | Variables | Conditions |
Data Types | Numbers |
Strings | Formatting | Operators | Generators |
Decorators | Functions
| Lists | Tuples | Sets | Dictionaries | Parameters | Arguments |
Arrays | Linked Lists
| Hash Tables | Binary Search Trees | Recursion | Sorting
Algorithms | Exception Handling | Serialization
🚀 Advanced Functions
RegEx | Decorators | Lambdas | Iterators | Classes | Inheritance | Methods | List Comprehensions | Generator Expressions | PyPi | PIP | Conda
💠 Frameworks
Django | Flask | CherryPy | Bottle | Dash | | PyTest | Scrapy | PyScript |
🗂 Libraries
TensorFlow | Scikit-Learn | Numpy | Keras | PyTorch | SciPy | Pandas | Theano | Seaborn | OpenCV | Bokeh | Matplotlib | Plotly | BeautifulSoup | SymPy | Pillow
🧰 Other Tools
Selenium | PyCharm | PyTest | Jupyter Notebook | Faker | PyGame | Tkinter
Learn Data Science
▶️ Basics
Linear Algebra | Databases | Tabular Data | Time Series | Extract, Transform, Load | Data Formats | Regular Expressions | Important libraries |
💻 Programming languages for Data Science
SQL | R | Python
🐍 Python for Data Science
Syntax | Variables | Data Types | Functions | Numbers | Operators | Important libraries
🔁 Data Sources
Data Mining | Web scraping | Public Data Sets
📊 Exploratory Data Analysis
Principal Component Analysis | Dimensionality Reduction | Normalization | Data Cleaning | Estimators | Feature Extraction | Sampling
🔢 Statistics
Probability Theory | Continuous Distribution | Summary Statistics | Estimation | Hypothesis Testing | Confidence Interval | Monte Carlo Methods
📈 Data Visualization + tools
Storytelling | Charts | Dashboards | Power BI | Tableau | R | Dash | Seaborn | Matplotlib | Bokeh | Plotly
Learn Machine Learning
📊 Data
Labeling | Exploration | Preprocessing | Splitting | Augmentation
🧮 Modeling
Baselines | Evaluations | Experiment tracking | Optimization
♻️ Algorithms
Supervised Learning | Unsupervised Learning | Ensemble Learning | Reinforcement Learning | Linear Regression | Logistic Regression | Decision Tree | Random Forrest | Support Vector Machines | Naive Bayes | KNN Classification | K-Means
🔌 Use Cases
Computer Vision | Natural Language Processing | Recommender Systems | Pattern recognition
🗂 Frameworks & Libraries
Django | Flask | Keras | Numpy | Pandas | Scikit-Learn | Tensorflow | Matplotlib | PyTorch | Scipy | Hugging Face
🧰 Other tools
Docker | Kubernetes | MLflow
Learn Deep Learning
🧠 Neural Networks
Artificial Neural Networks | Convolutional Neural Networks | Recurrent Neural Networks | Transformers | Generative Adversarial Networks | Long Short Term Memory Networks
🧮 Training Methods
Optimizers | Learning Rate Schedule | Batch Normalization | Batch Size Effects | Regularization | Multi-task Learning | Transfer Learning
🗂 Frameworks & Libraries
Langchain | Django | Flask | Keras | Numpy | Pandas | Scikit-Learn | Tensorflow | Matplotlib | PyTorch | Scipy | Hugging Face
🧰 Other tools
Docker | Kubernetes | MLflow