Zero to Machine Learning Hero
(AI, Machine Learning & Deep Learning with Python)
Day 1 – 3:
Python Language Fundamentals
- Jupyter Notebook
- Object and Data Structure (numbers, lists, dictionaries, tuples, files, sets, booleans)
- Comparison Operators
- Statements (if and else, for loops, while loops, list comprehensions)
- Methods and Functions
- Object Oriented Programming
- Errors and Exception Handling
- Built-in Functions (map, reduce, filter, zip, enumerate)
Day 4 – 5:
Data Analysis & Visualization
- Pandas: Data Preprocessing (missing data, categorical data, feature scaling), Data Transformation, Data Wrangling
- NumPy: Array, Array Indexing, Array Math, Array Manipulation
- Matplotlib (2D plotting & charting)
Day 1 – 3:
Machine Learning with Scikit-Learn
- Regression (Linear Regression, Decision Tree Regression, Random Forest Regression), Classification (Logistic Regression, KNN, SVM, NaÏve Bayes, Decision Tree, Random Forest), K-Fold Cross Validation
- Project / Use Case: Tabular Prediction (Regression/Calssification)
Day 4 – 5:
Deep Learning with Tensorflow and Keras
- Artificial Neural Network (ANN), Initialization, Activation Functions, Cost Functions, Gradient Descent, Backpropagation, Learning Rate, Optimizers, Regularization, Batch Normalization, Dropout
- Natural Language Processing: NLTK, SpaCy, Tokenization, Embedding, Recurrent Neural Network (RNN), LSTM, GRU
- Computer Vision: ConvNet, pooling, CNN
- Project / Use Case:
a. Image Classification
b. Sentiment Analysis (NLP)
Contact Information
+60 17-282 8183
P37, Kelana Square,
Jalan SS7/26, Kelana Jaya,
47301 Petaling Jaya, Selangor.
