Machine Learning using Python and R
Become a Machine Learning (ML) specialist with the Machine Learning using Python and R programme. Gain holistic knowledge in ML algorithms and applications using the two most popular programming language. 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.
On-campus training in Malaysia: 32 hours
Machine Learning Course Overview
Machine Learning Training using Python and R programming includes an overview of analytical techniques used to manipulate humongous data and how to draw meaningful business insights from the same. The course modules instruct the student on the various techniques used to analyze structured and unstructured data, building advanced prediction models with machine learning algorithms and data visualization. The course is laden with practical case studies which enable the participants to solve complex business problems and improve profitability in their companies.
Machine Learning Training Outcomes
Certified Machine Learning Course Modules
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.
In Malaysia, the national average salary of a machine learning engineer is RM 141,958 per annum.
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Who Should Sign Up?
- Candidates aspiring to be Data Scientist, Machine Learning Expert, Analytics Manager / Professional, Business Analyst, Data Analyst, etc.
- Employees of organizations which are planning to devise proactive strategies using Machine Learning approaches
- Managers with knowledge of basic programming and decision-makers who want to make data-driven decisions
- Graduates who are looking to build a career in Machine Learning, Data Science and Data Analytics Professionals
- Mid-level and Senior-level Executives who wish to learn predictive decision making
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.
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Machine Learning Tutorial Panel of Coaches
Bharani Kumar Depuru
- Areas of expertise: Data Analytics, Digital Transformation, Industrial Revolution 4.0.
- Over 14+ years of professional experience.
- Trained over 2,500 professionals from eight countries.
- Corporate clients include Hewlett Packard Enterprise, Computer Science Corporation, Akamai, IBS Software, Litmus7, Personiv, Ebreeze, Alshaya, Synchrony Financials, Deloitte.
- Professional certifications - PMP, PMI-ACP, PMI-RMP from Project Management Institute, Lean Six Sigma Master Black Belt, Tableau Certified Associate, Certified Scrum Practitioner, AgilePM (DSDM Atern).
- Alumnus of Indian Institute of Technology, Hyderabad and Indian School of Business.
Sharat Chandra Kumar
- Areas of expertise: Data Science, Machine Learning, Business Intelligence and Data Visualisation.
- Trained over 1,500 professional across 12 countries.
- Worked as a Data Scientist for 14+ years across several industry domains.
- Professional certifications: Lean Six Sigma Green and Black Belt, Information Technology, Infrastructure Library.
- Experienced in Big Data Hadoop, Spark, NoSQL, NewSQL, MongoDB, R, RStudio, Python, Tableau, Cognos.
- Corporate clients include DuPont, All-Scripts, Girnarsoft (College-dekho, Car-dekho) and many more.
- Areas of expertise: Data Science, Machine Learning, Business Intelligence and Data Visualisation.
- Over 20+ years of industry experience in Data Science and Business Intelligence.
- Trained professionals from Fortune 500 companies and students from prestigious colleges.
- Experienced in Cognos, Tableau, Big Data, NoSQL, NewSQL.
- Corporate clients include Time Inc., Hewlett Packard Enterprise, Dell, Metric Fox (Champions Group), TCS and many more.
Get validation of your advanced skills and knowledge with the Machine Learning using Python &R certificate. Join the growing community of developers and data scientists trained on Python and R.
FAQs on Machine Learning Training Course
Yes.You will get a certificate at the end of the course from 360DigiTMG.
The most popular tools Python and R and their Machine learning packages like sklearn and various other R packages will be covered in the course. These tools can be used to write Machine Learning algorithms, Neural Network techniques and Predictive Modelling with Regression Analysis.
Heng Nguan Ting8 months ago
A company that give course from beginning level to advanced level. They will always keep in touch with their participant in order to get know about them and solve their problem accordingly. Nice place to start your learning.
Puteri ameena9 months ago
I joined the Data Science using R workshop and I really appreciated all the efforts that have been put into sharing the knowledge of Data Science. I learnt the reality of handling data unlike the theoretical classes we normally learn in university. I had so much fun too!! Thank you
Rong An Kiew9 months ago
I took part in the Jumpstart program 2018, I gained a lot of knowledge about Big Data from this program and there are also some experienced tutors teaching in this program. It provides some assignments to let us practise. Overall it is a good platform for learning Big Data.