5 Days Machine Learning Specialization
Venue
Entrance Fee
Category
Event Type
Share
Schedule
Date | Time |
---|---|
19/02/2024 | 9:30 AM - 5:30 PM |
20/02/2024 | 9:30 AM - 5:30 PM |
21/02/2024 | 9:30 AM - 5:30 PM |
22/02/2024 | 9:30 AM - 5:30 PM |
23/02/2024 | 9:30 AM - 5:30 PM |
18/03/2024 | 9:30 AM - 5:30 PM |
19/03/2024 | 9:30 AM - 5:30 PM |
20/03/2024 | 9:30 AM - 5:30 PM |
21/03/2024 | 9:30 AM - 5:30 PM |
22/03/2024 | 9:30 AM - 5:30 PM |
15/04/2024 | 9:30 AM - 5:30 PM |
16/04/2024 | 9:30 AM - 5:30 PM |
17/04/2024 | 9:30 AM - 5:30 PM |
18/04/2024 | 9:30 AM - 5:30 PM |
19/04/2024 | 9:30 AM - 5:30 PM |
13/05/2024 | 9:30 AM - 5:30 PM |
14/05/2024 | 9:30 AM - 5:30 PM |
15/05/2024 | 9:30 AM - 5:30 PM |
16/05/2024 | 9:30 AM - 5:30 PM |
17/05/2024 | 9:30 AM - 5:30 PM |
10/06/2024 | 9:30 AM - 5:30 PM |
11/06/2024 | 9:30 AM - 5:30 PM |
12/06/2024 | 9:30 AM - 5:30 PM |
13/06/2024 | 9:30 AM - 5:30 PM |
14/06/2024 | 9:30 AM - 5:30 PM |
15/07/2024 | 9:30 AM - 5:30 PM |
16/07/2024 | 9:30 AM - 5:30 PM |
17/07/2024 | 9:30 AM - 5:30 PM |
18/07/2024 | 9:30 AM - 5:30 PM |
19/07/2024 | 9:30 AM - 5:30 PM |
12/08/2024 | 9:30 AM - 5:30 PM |
13/08/2024 | 9:30 AM - 5:30 PM |
14/08/2024 | 9:30 AM - 5:30 PM |
15/08/2024 | 9:30 AM - 5:30 PM |
16/08/2024 | 9:30 AM - 5:30 PM |
09/09/2024 | 9:30 AM - 5:30 PM |
10/09/2024 | 9:30 AM - 5:30 PM |
11/09/2024 | 9:30 AM - 5:30 PM |
12/09/2024 | 9:30 AM - 5:30 PM |
13/09/2024 | 9:30 AM - 5:30 PM |
14/10/2024 | 9:30 AM - 5:30 PM |
15/10/2024 | 9:30 AM - 5:30 PM |
16/10/2024 | 9:30 AM - 5:30 PM |
17/10/2024 | 9:30 AM - 5:30 PM |
18/10/2024 | 9:30 AM - 5:30 PM |
11/11/2024 | 9:30 AM - 5:30 PM |
12/11/2024 | 9:30 AM - 5:30 PM |
13/11/2024 | 9:30 AM - 5:30 PM |
14/11/2024 | 9:30 AM - 5:30 PM |
15/11/2024 | 9:30 AM - 5:30 PM |
09/12/2024 | 9:30 AM - 5:30 PM |
10/12/2024 | 9:30 AM - 5:30 PM |
11/12/2024 | 9:30 AM - 5:30 PM |
12/12/2024 | 9:30 AM - 5:30 PM |
13/12/2024 | 9:30 AM - 5:30 PM |
This Machine Learning Specialization introduces you to the exciting, high-demand field of Machine Learning. Through a series of hand on practical exercises, you will gain applied experience in major areas of Machine Learning including Prediction, Classification, Clustering, Computer Vision and Deep Learning. You will learn to analyze data and build intelligent applications that can make predictions from data.
This five days classroom facilitator Machine Learning Specialisation course will build your fundation in Python first, then follow by classical Machine Learning using Scikit Learn, follow by Deep Learning using Tensorflow 2.x framework.
Certificate
All participants will receive a Certificate of Completion from Tertiary Courses after achieved at least 75% attendance.
Funding and Grant
HRD Corp Claimable Course for Employers Registered with HRD Corp
>Day 1
Topic 1 - Python Fundamental
Topic 1.1 Get Started on Python
- Overview of Python
- Set Python
- Code Your First Python Script
Topic 1.2: Data Types
- Number
- String
- List
- Tuple
- Dictionary
- Set
Topic 1.3 Operators
- Arithmetic Operators
- Compound Operators
- Comparison Operators
- Membership Operators
- Logical Operators
Topic 1.4 Control Structure, Loop and Comprehension
- Conditional
- Loop
- Iterating Over Multiple Sequences
- Comprehension
Topic 1.5 Function
- Function Syntax
- Return Values
- Default Arguments
- Variable Arguments
- Lambda, Map, Filter
Topic 1.6 Modules & Packages
- Import Modules and Packages
- Python Standard Packages
- Third Party Packages
Day 2
Topic 2 - Data Analytics and Visualization with Python
Topic 2.1 Data Preparation
- Data Analytics with Pandas
- Pandas DataFrame and Series
- Import and Export Data
- Filter and Slice Data
- Clean Data
Topic 2.2 Data Transformation
- Join Data
- Transform Data
- Aggregate Data
Topic 2.3 Data Visualization
- Data Visualization with Matplotlib and Seaborn
- Visualize Statistical Relationships with Scatter Plot
- Visualize Categorical Data with Bar Plot
- Visualize Correlation with Pair Plot and Heatmap
- Visualize Linear Relationships with Regression
Topic 2.4 Data Analysis
- Statistical Data Analysis
- Time Series Analysis
Topic 2.5 Advanced Data Analytics
- Data Piping
- Groupby and Apply Custom Functions
- Linear Regression
Day 3
Topic 3 Machine Learning with Scikit Learn
Topic 3.1 Overview of Machine Learning and Scikit Learn
- Introduction to Machine Learning
- Supervised vs Unsupervised Learnings
- Machine Learning Applications and Case Studies
- What is Scikit Learn
- Installing Scikit-Learn
Topic 3.2 Classification
- What is Classification
- Classification Algorithms
- Classification Workflow
- Confusion Matrix
- Binary Classification Metrics
- ROC and AUC
Topic 3.3 Regression
- What is Regression?
- Regression Algorithms
- Regression Workflow
- Regression Metrics
- Overfitting and Regularizations
Topic 3.4 Clustering
- What is Clustering
- K-Means Clustering
- Silhouette Analysis
- Dendrogram and Hierarchical Clustering
Topic 3.5 Principal Component Analysis
- Curse of Dimensionality Issue
- What is Principal Component Analysis (PCA)
- Feature Reduction with PCA
Day 4
Topic 4 Basic Neural Network with Tensorflow
Topic 4.1 Introduction to Deep Learning
- Machine Learning vs Deep Learning
- Deep Learning Methodology
- Overview of Tensorflow Keras
- Install and Run Tensorflow Keras
- Basic Tensorflow Keras Operations
Topic 4.2 Neural Network for Regression
- What is Neural Network (NN)?
- Loss Function and Optimizer
- Build a Neural Network Model for Regression
Topic 4.3 Neural Network for Classification
- One Hot Encoding and SoftMax
- Cross Entropy Loss Function
- Build a Neural Network Model for Classification
Day 5
Topic 5 Advanced Neural Networks with Tensorflow
Topic 5.1 Convolutional Neural Network (CNN)
- Introduction to Convolutional Neural Network?
- ImageDataGenerator
- Image Classification Model with CNN
- Data Augmentation and Dropout
Topic 5.2 Transfer Learning
- Introduction to Transfer Learning
- Applications of Pre-Trained Models
- Fine Tuning Pre-Trained Models
Topic 5.3 Recurrent Neural Network (RNN)
- Introduction to Recurrent Neural Network (RNN)
- LSTM and GRU
- Build a RNN Model for Time Series Forecasting
- Build a RNN Model for Sentiment Analysis