Machine Learning with Python: Complete Training Course
Master cutting-edge machine learning techniques with Python under expert guidance. Enroll in our comprehensive training program designed specifically for aspiring data scientists seeking practical skills in classification, regression, clustering, neural networks, and real-world application deployment.
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What you'll learn
- Implement supervised and unsupervised machine learning algorithms using Python
- Create ensemble learning systems combining multiple machine learning models
- Build classification models using scikit-learn and evaluate their performance
- Deploy machine learning models into web applications with database integration
- Design neural networks for image recognition with backpropagation training
- Apply data preprocessing techniques including feature selection and cleaning
- Perform sentiment analysis on text data using natural language processing
- Develop regression models for predicting continuous target variables
Why should you attend?
This comprehensive course provides a thorough foundation in machine learning concepts and practical implementation using Python. Students begin by exploring fundamental machine learning definitions, concepts, and the three primary types of learning: supervised, unsupervised, and reinforcement learning. The curriculum covers essential Python libraries including pandas, NumPy, and scikit-learn for data analysis and machine learning implementation. The course progresses through classification algorithms, starting with building intuition and implementing perceptron and linear classification algorithms from scratch. Students then advance to using scikit-learn for popular classification methods, including logistic regression and Support Vector Machines (SVM) with kernel methods. Critical data preprocessing techniques are covered extensively, including handling missing data, categorical variables, and feature selection strategies. Advanced topics include dimensionality reduction through Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA), model evaluation using cross-validation, hyperparameter tuning via grid search, and ensemble learning methods. Practical applications feature sentiment analysis with text data processing, web application development for model deployment, regression analysis for continuous variables, clustering analysis for unlabeled data, and artificial neural networks for image recognition with backpropagation implementation.
Course Syllabus
Day 1 - ML Fundamentals and Classification
Short Break
15 minsRecap and Q&A
15 minsLunch
1 hourShort Break
15 minsRecap and Q&A
15 minsEnd of Day 1
Day 2 - Model Optimization and Evaluation
Short Break
15 minsRecap and Q&A
15 minsLunch
1 hourShort Break
15 minsRecap and Q&A
15 minsEnd of Day 2
Day 3 - Advanced Applications and Deployment
Short Break
15 minsRecap and Q&A
15 minsLunch
1 hourShort Break
15 minsRecap and Q&A
15 minsEnd of Day 3
Ratings and Reviews
Instructor
Instructor
Instructor
Instructor
Dr. Esther Suria Kala is a highly accomplished ICT consultant and corporate trainer with nearly 30 years of extensive experience in information technology, project management, and organizational development. As the founder of Angel Software Solutions, she has established herself as a versatile and dedicated professional who delivers cutting-edge training solutions across Malaysia and internationally.
Her academic credentials are exceptional, including a PhD in Psychology with a focus on Human Behaviour and Human Resources, an MBA in Finance, and degrees in both Computer Science and Human Resources. Currently pursuing a second PhD in IT Information Security, Dr. Esther demonstrates an unwavering commitment to continuous learning and staying at the forefront of technological advancement. Her educational foundation is complemented by an impressive array of professional certifications, including Microsoft Certified Trainer (MCT), CISSP, ITIL, SAP Certified Associate, Certified Cyber Security Professional, Data Scientist, AI Engineering, and ECBA certifications.
Dr. Esther's technical expertise spans an extensive range of domains, from traditional programming languages like Java, C++, and PHP to modern technologies including Python, AI coding, machine learning, RPA, and IR 4.0 microservices. She is proficient in database management systems including Microsoft SQL Server and Oracle, web development frameworks, and enterprise solutions like SAP Crystal Reports and SharePoint Server. Her knowledge extends to cybersecurity, ethical hacking, network administration, and data analytics, making her uniquely qualified to address both technical and strategic business challenges.
As a trainer, Dr. Esther excels in bridging the gap between technical complexity and practical application. She delivers comprehensive training programs for both IT and non-IT professionals, covering everything from software development and cloud computing to soft skills such as digital marketing, business analysis, customer service, and project management. Her ability to communicate effectively in both English and Bahasa Malaysia enables her to connect with diverse audiences across different organizational levels.
Her impressive client portfolio includes leading organizations such as Maybank, Telekom Malaysia, Malaysian Airlines, Tenaga Nasional Berhad, Bank Negara, Ministry of Education, Ministry of Finance, and numerous multinational corporations. This extensive experience across banking, telecommunications, government, aviation, and technology sectors demonstrates her adaptability and deep understanding of varied industry requirements. Recognized with the Outstanding Achievement Award in Information Technology from University Malaya in 2013, Dr. Esther continues to empower organizations through innovative training solutions that drive digital transformation and professional excellence.
Instructor
Instructor
Course Reviews
"The course does add all the skills mentioned. The content is good with thoughtful exercises. Definitely a good starting point for Machine Learning. Can recommend this course if you are new to any of the skills."
"The course does add all the skills mentioned. The content is good with thoughtful exercises. Definitely a good starting point for Machine Learning. Can recommend this course if you are new to any of the skills."
"Very well taught course. A lot of knowledge provided in an interactive manner and it wasn't overwhelming."
Instructor Reviews
Mohammad Mehdi Lotfinejad
Chief Data Officer & Data Science Trainer"Mehdi and I worked on several projects with company such as Petronas , Shell and CIMB Regional ETC. I must say Mehdi's training was highly appreciated by our clients as he was able to exhibit in full display his vast knowledge as a Data professional. I would highly recommend him to anyone looking for a top tier training expert."
"Not only knowledgeable but also having hands dirty on what he knows Friendly and building networks quickly."
"I had the pleasure of working with Mehdi together on some high-level initiatives such as the Petronas data scientist program and Shell's project to become a data-driven organization. During these projects, Mehdi received numerous accolades for his ability to share his knowledge and mentor up-and-coming data scientists. Based on our shared experiences, I have no hesitation in recommending Mehdi for any project or position he may be considered for."
FAQ
Frequently Asked Questions About This Course
Why should you attend?
This comprehensive course provides a thorough foundation in machine learning concepts and practical implementation using Python. Students begin by exploring fundamental machine learning definitions, concepts, and the three primary types of learning: supervised, unsupervised, and reinforcement learning. The curriculum covers essential Python libraries including pandas, NumPy, and scikit-learn for data analysis and machine learning implementation. The course progresses through classification algorithms, starting with building intuition and implementing perceptron and linear classification algorithms from scratch. Students then advance to using scikit-learn for popular classification methods, including logistic regression and Support Vector Machines (SVM) with kernel methods. Critical data preprocessing techniques are covered extensively, including handling missing data, categorical variables, and feature selection strategies. Advanced topics include dimensionality reduction through Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA), model evaluation using cross-validation, hyperparameter tuning via grid search, and ensemble learning methods. Practical applications feature sentiment analysis with text data processing, web application development for model deployment, regression analysis for continuous variables, clustering analysis for unlabeled data, and artificial neural networks for image recognition with backpropagation implementation.
What you'll learn
- Implement supervised and unsupervised machine learning algorithms using Python
- Create ensemble learning systems combining multiple machine learning models
- Build classification models using scikit-learn and evaluate their performance
- Deploy machine learning models into web applications with database integration
- Design neural networks for image recognition with backpropagation training
- Apply data preprocessing techniques including feature selection and cleaning
- Perform sentiment analysis on text data using natural language processing
- Develop regression models for predicting continuous target variables
Course Syllabus
Day 1 - ML Fundamentals and Classification
Short Break
15 minsRecap and Q&A
15 minsLunch
1 hourShort Break
15 minsRecap and Q&A
15 minsEnd of Day 1
Day 2 - Model Optimization and Evaluation
Short Break
15 minsRecap and Q&A
15 minsLunch
1 hourShort Break
15 minsRecap and Q&A
15 minsEnd of Day 2
Day 3 - Advanced Applications and Deployment
Short Break
15 minsRecap and Q&A
15 minsLunch
1 hourShort Break
15 minsRecap and Q&A
15 minsEnd of Day 3
Course Reviews
"The course does add all the skills mentioned. The content is good with thoughtful exercises. Definitely a good starting point for Machine Learning. Can recommend this course if you are new to any of the skills."
"The course does add all the skills mentioned. The content is good with thoughtful exercises. Definitely a good starting point for Machine Learning. Can recommend this course if you are new to any of the skills."
"Very well taught course. A lot of knowledge provided in an interactive manner and it wasn't overwhelming."
Instructor Reviews
Mohammad Mehdi Lotfinejad
Chief Data Officer & Data Science Trainer"Mehdi and I worked on several projects with company such as Petronas , Shell and CIMB Regional ETC. I must say Mehdi's training was highly appreciated by our clients as he was able to exhibit in full display his vast knowledge as a Data professional. I would highly recommend him to anyone looking for a top tier training expert."
"Not only knowledgeable but also having hands dirty on what he knows Friendly and building networks quickly."
"I had the pleasure of working with Mehdi together on some high-level initiatives such as the Petronas data scientist program and Shell's project to become a data-driven organization. During these projects, Mehdi received numerous accolades for his ability to share his knowledge and mentor up-and-coming data scientists. Based on our shared experiences, I have no hesitation in recommending Mehdi for any project or position he may be considered for."
Public Pricing
Corporate Pricing
Pax:
Training Provider Pricing
Pax:
Features
Subsidies
Ratings and Reviews
Instructors
Dr. Esther Suria Kala is a highly accomplished ICT consultant and corporate trainer with nearly 30 years of extensive experience in information technology, project management, and organizational development. As the founder of Angel Software Solutions, she has established herself as a versatile and dedicated professional who delivers cutting-edge training solutions across Malaysia and internationally.
Her academic credentials are exceptional, including a PhD in Psychology with a focus on Human Behaviour and Human Resources, an MBA in Finance, and degrees in both Computer Science and Human Resources. Currently pursuing a second PhD in IT Information Security, Dr. Esther demonstrates an unwavering commitment to continuous learning and staying at the forefront of technological advancement. Her educational foundation is complemented by an impressive array of professional certifications, including Microsoft Certified Trainer (MCT), CISSP, ITIL, SAP Certified Associate, Certified Cyber Security Professional, Data Scientist, AI Engineering, and ECBA certifications.
Dr. Esther's technical expertise spans an extensive range of domains, from traditional programming languages like Java, C++, and PHP to modern technologies including Python, AI coding, machine learning, RPA, and IR 4.0 microservices. She is proficient in database management systems including Microsoft SQL Server and Oracle, web development frameworks, and enterprise solutions like SAP Crystal Reports and SharePoint Server. Her knowledge extends to cybersecurity, ethical hacking, network administration, and data analytics, making her uniquely qualified to address both technical and strategic business challenges.
As a trainer, Dr. Esther excels in bridging the gap between technical complexity and practical application. She delivers comprehensive training programs for both IT and non-IT professionals, covering everything from software development and cloud computing to soft skills such as digital marketing, business analysis, customer service, and project management. Her ability to communicate effectively in both English and Bahasa Malaysia enables her to connect with diverse audiences across different organizational levels.
Her impressive client portfolio includes leading organizations such as Maybank, Telekom Malaysia, Malaysian Airlines, Tenaga Nasional Berhad, Bank Negara, Ministry of Education, Ministry of Finance, and numerous multinational corporations. This extensive experience across banking, telecommunications, government, aviation, and technology sectors demonstrates her adaptability and deep understanding of varied industry requirements. Recognized with the Outstanding Achievement Award in Information Technology from University Malaya in 2013, Dr. Esther continues to empower organizations through innovative training solutions that drive digital transformation and professional excellence.
FAQ
Frequently Asked Questions About This Course
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