Funding programmes
IBF-STS
GICT is accredited by the Institute of Banking and Finance (IBF) as an IBF-STS Accredited Training Provider.
Certified Machine Learning Specialist (CMLS) Course
Course Description
The Certified Machine Learning Specialist (CMLS) program is aimed at aspiring data practitioners, from data analysts to data scientists. It provides a high-level overview of concepts, data manipulation techniques, and machine learning algorithms using the Python programming language, which is one of the world’s most versatile programming languages and tools such as RapidMiner and Weka.
Course Objective
The objective is to equip participants with practical skills to implement classification models and regression models using various supervised learning algorithms such as linear and logistic regression models, k-nearest neighbors, neural networks, support vector machine, decision trees and ensemble methods such as random forest. Participants will also acquire the skills related to the implementation of unsupervised learning algorithms such as k-means clustering and other analytical methods such as correlation analysis and association rules to derive insights from their data.
Skills Acquired
Participants will be equipped with practical end-to-end machine learning skillsets such as engineering classification and regression models using Support Vector Machines (SVM), Decision Trees, Bayesian Networks, Neural Network, and ensemble model such as Random Forest to name a few. In addition, participants will be equipped with the knowledge of validating the engineered model using cross-validation methodology and interpreting the performance of the model using a performance matrix. Participants stand to gain industry-ready practical skills such as Scikit-Learn, NumPy, Pandas, SciPy and Tensorflow.
Why Machine Learning Course ?
Anyone who wish to get skilled in Machine Learning using Python programming is recommended to participate in this program. It is designed for non-technical and technical professionals, however those with programing background in any languages will be advantageous.
Machine Learning and Artificial Intelligence is gathering momentum to be one of the key pillars of the next Industry Revolution.
Course Outline
- Unit 1: Introduction and basic concepts in Machine learning
- Unit 2: Introduction to theories used in Machine Learning
- Unit 3: Supervised learning vs. Unsupervised learning
- Unit 4: Model selection in Machine learning
- Unit 5: Role of Weka in Machine Learning
- Unit 6: Decision Tree and Rule mining using Weka
- Unit 7: A Brief review on SciPy
- Unit 8: Random Forest and Markov Decision Process algorithm
- Unit 9: Google's Go Programming with k-nearest neighbors algorithm
- Unit 10: C 5.0 based decision tree algorithm
Course Outcome
- Acquire knowledge of AI and machine learning and its impact on enterprises with several use cases
- Acquire knowledge on machine learning techniques: Supervised, Unsupervised & Reinforcement Learning
- Gain a solid understanding of the usage of ReLU as a deep learning-activation function and learning rate
- Gain a solid understanding of discriminative and generative algorithms
- Gain a solid understanding of key concepts like Principal Component Analysis (PCA),Hyperparameter tuning with Grid Search, Clustering, Classification, Regression & Neural Network
Please feel free to contact us if you require further information on our GICT Training and Certification courses.