Certificate Course in
Machine Learning using Python and R
- 32 Hours Classroom & Live Online Sessions
- 80+ Hours Assignments & Real-Time Projects
- IBM Digital Certificates and Badges
- Complimentary Python and R Programming Beginners Course
Machine Learning Course Overview
Become a Machine Learning (ML) specialist with the Machine Learning using Python and R program in Malaysia. Gain holistic knowledge of ML algorithms and applications using the two most popular programming languages. Use Python and R to enable regression analysis and to build predictive models. Orient yourselves with Black Box techniques like Neural Networks and Support Vector Machine. Machine Learning Training using Python and R programming includes an overview of analytical techniques used to manipulate massive amounts of data and then driving meaningful business insights from the same. The course module demonstrates the various techniques used to analyze structured and unstructured data, build advanced prediction models with Machine Learning algorithms and Data Visualization. The course is loaded with practical case studies that enable the participants to solve complex business problems and improve profitability in their companies.
What is Machine Learning?
Every time we create new technology, we create a bigger buzz. Two major technologies sweeping the market are Artificial intelligence (AI) and Machine learning (ML). Machine Learning is a subset of Artificial Intelligence that focuses on designing systems that enable a machine to perform tasks without explicit coding. All the Artificial Intelligence advancements we hear about and the applications we see are all a result of Machine Learning Algorithms. Machine-learning Algorithms use a huge amount of data and statistics to find patterns and inferences it collects from the statistical models and complex algorithms.
What is R?
R is primarily a statistical software developing tool specifically tailored for statistical computing as well as graphical processing of data. It is an interpreter-based language and is very popular across multiple industries. R is used for data analysis, statistical modeling, time series forecasting clustering, etc. CRAN (Comprehensive R Archive Network) repository is R’s biggest strength with 7700+ packages that are specialized for all sorts of data analytical needs.
What is Python?
Python has emerged as a high-level programming language suitable for a variety of tasks in machine learning. With its simple, easy to understand syntax clubbed with its edit-test-debug cycle makes it a popular choice among programmers. Python is used for developing software, management of infrastructure, and data analysis. The biggest asset of the language is its collection of libraries and frameworks which can be utilized for Machine Learning, Automation, Web development, etc.
Machine Learning Training Outcomes
Machine learning aims to learn from data and then make precise predictions without having to be explicitly programmed. In this course, you will learn to design and implement machine learning solutions to solve the problems of classification, regression, and clustering. You will also learn to evaluate and interpret the results of the various machine learning algorithms. Machine learning programmers provide program services from the customized news feed to tailored web searches, they also build pipelines to connect with the data that enables the machine to learn and provide optimizing solutions for performance and scalability. Students will also understand the popular machine learning approaches and the underlying mathematical relationships between the various algorithms. Students will explore the process of investigating data to solve predictive tasks, such as speech recognition, object recognition, automatic algorithm configuration, time series forecasting, machine translation, and much more. This course will also give students a chance to understand the fundamental issues and challenges of machine learning which include data, model selection, and model complexity. This course in machine learning equips you with the necessary skills needed to excel in this field. By the end of the training program, you will
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Who Should Sign Up?
- Candidates aspiring to be Data Scientist, Machine Learning Expert, Data Analyst, etc.
- Employees of organizations
- Managers with knowledge of basic programming and decision-makers
- Mid-level and Senior-level Executives
- Data Science and Data Analytics Professionals
Certified Machine Learning Course Modules
This Module provides an easily understandable overview of machine learning. This training program in Machine learning facilitates an all-round development of knowledge that can be put to effective use to help organizations promote cognitive technology. In this course, you will learn about the two most popular programming languages used for Data Analysis, Machine Learning, and Artificial Intelligence. If you are a non-programmer, you will kick start your programming skills from this point. In this module, you will learn how to extract tables from traditional database MySQL using Python and R. You also will learn about the various functions and packages involved in Data Extraction. In this module, you will also learn about RStudio which is the primer IDE for R and understand why Python and the IDE are used by Data Analysts worldwide.
In this Programming tutorial, you will learn about the two most popular programming languages used for Data Analysis, Machine Learning and Artificial Intelligence. Learn to install Python and R on your systems (Windows, Mac, or Linux machine). You will learn about the CRAN repository and R packages. In this module, you will learn about RStudio which is the primer IDE for R. Understand Python and the IDE used by Data Analysts worldwide. Learn about the libraries commonly used in Python. If you are a non-programmer, you will kick start your programming skills from this point.
Data can be stored in various sources. Traditionally organizations store data in RDBMS databases. In this module, you will learn how to extract tables from traditional database MySQL using Python and R. You also will learn about the various functions and packages involved in Data Extraction.
Understand the holistic view of Machine Learning concepts. Learn about the Project Management of Machine Learning projects and various concepts for performing Descriptive Analytics, like EDA, Imputation, Visualizations, etc. As part of this module, participants will learn about the basics of Python and R. They will also learn the basic concepts of scripting Machine Learning algorithms.
Learn about inferential statistics and understand sampling. Learn about various sampling techniques as part of this module. In this module, you will also learn about Balanced Datasets. In the real world, data sets are largely imbalanced. Learn to deal with Imbalanced Datasets using advanced Data Analytics techniques.
Descriptive analytics will explain the historical events that have occurred. Learn to perform statistical calculations on data, to find patterns and anomalies, to derive insights for the business. Understand the various functions and packages used to perform statistical computing using Python and R. Learn how Data visualizations can help tell stories using plots. In this module, you will also learn about various visualization techniques for Uni-variate and Bi-variate Data Analysis.
Machine Learning is used for performing predictions on data. To develop an appropriate model, discerning underlying patterns in the data is of paramount importance. As part of descriptive analytics, you will learn about various data manipulation techniques to preprocess the data. These techniques will help you identify patterns in the data. Learn about Imputation techniques, Feature Engineering, Data Wrangling, Data Modification techniques like transformations and normalization using Python and R.
Machine learning is a process of training the machine to understand a pattern and define a mathematical equation that explains the relationship between dependent and independent variables. Python and R are functional oriented programming languages that use packages or libraries that provide functions to perform training on the business data. In this module, you will learn about various functions and libraries which are used to perform Descriptive and Predictive Analytics.
Data Mining is a process of analyzing data using mathematical concepts to uncover hidden facts from data. Use Python and R Programming to develop a wide variety of Machine Learning algorithms. Understand the implementation and evaluation of ML techniques by understanding measures of Error (RMSE). Learn about problems like Heteroscedasticity, Overfitting and Underfitting, Imbalance in the data and solving them using Python and R functions.
Learn about the interpretable techniques to perform predictive analytics. Understand how to perform Regression analysis on numeric dependent variables. Learn to decode the relation between dependent and independent variables using correlation analysis and scatter diagram. Understand why Causation cannot be estimated using Correlation. Learn about the packages used in Python and R for training Regression models. Learn about model accuracy improvement techniques. In this module, you will learn about the Confusion matrix and conditions of confusion matrix which are used to evaluate the binary classification logistic regression model.
The most commonly used rules-based algorithms, Decision tree, and Random forest are used for classifying dependent variables. In this tutorial, learn about the nodes used to create rules in Decision trees. Understand the information calculation using entropy to create pure classes in Decision tree analysis. Learn about pruning and its necessity. Understand the ensemble techniques for Decision Tree examples and learn about the Random forest algorithm.
Machine Learning Trends in Malaysia
The demand for machine learning jobs in Malaysia outstrips the supply. There is a mad rush to learn Machine Learning using Python and R and a number of institutes for machine learning have mushroomed in Malaysia. These institutes conduct numerous workshops on machine learning with Python and R. One of the most reliable training institutes is 360DigiTMG. 360DigiTMG offers a course titled " Machine Learning with Python and R". The training includes understanding the entire Machine Learning Project life-cycle as well as understanding various machine learning algorithms ranging from Decision Tree to Ensemble models. 360DigiTMG is one of the premium training institutes which also offers machine learning internship opportunities in Malaysia.
Malaysia, a small country in South East Asia is firmly placed on the global map for its many historical and technological marvels, chief among them, being the Petronas Towers. At the time of its completion, it was the tallest structure in the world. Petronas is one of the largest and most profitable conglomerates based out of Malaysia having varied business interests in the petroleum sector. Many organizations in Malaysia are relying on the power of Machine Learning to make predictive business decisions. There are very lucrative career opportunities for professionals trained in Machine Learning and Artificial Intelligence. Python and R are the preferred programming languages in Malaysian IT circles.
How We Prepare You
Additional Assignments of over 60 hours
Live Free Webinars
Resume and LinkedIn Review Sessions
6 Months Access to LMS
Job Assistance in Machine Learning Fields
Unlimited Mock Interview and Quiz Session
Hands-on Experience in a Live Project
Life Time Free Access to Industry Webinars
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