Certificate Course in
Data Science Course in Singapore
- 48 Hours Classroom & Online Sessions
- 80+ Hours Assignments & eLearning
- 100% Job Assistance
- 2 Capstone Projects
- Industry Placement Training
- HRDF SBL-KHAS Claimable!
"The demand for Data Scientists to grow exponentially in the Asia-Pacific region. The Philippines will need 340,890 data scientists and Malaysia 21,000 by the year 2022." - (Source). Data science is an ever-evolving field and one needs to stay constantly updated about the industry be it the programming languages, the tools used, or advancements in associated fields like Artificial intelligence, Machine Learning, IoT, and more. The massive generation of data and the requirement for techniques to obtain valuable insight on it has led to an urgent requirement for talented professionals with adequate data science skills. It is predicted that by 2026, there will be at least one data interaction every 18 seconds between people connected via the internet and also because of billions of IoT devices connected which is going to create 95 ZB of data by 2026. Join this course on Data Science in Singapore and explore the most popular field in the world today with 360digiTMG.
- Computer Skills
- Basic Programming Knowledge
- Analytical Mindset
Data Science Certificate Course Overview
Fast-track your career with the Certification Programme in Data Science. Master all the keytools and techniques in Data Science and pick up domain-specific skills to add more value to your profile. The Certification Programme in Data Science is one of the most comprehensive courses in Singapore and the region. It is specially designed to suit both data professionals and beginners who want to make a career in this fast-growing profession. Over six days, students will learn key techniques such as Statistical Analysis, Regression Analysis, Data Mining, Machine Learning, Forecasting and Text Mining, and tools such as Python and R Programming.
What is Data Science?
Data Science is an ensemble of various tools, algorithms, and machine learning principles to discover patterns from unstructured data which when analyzed is primarily used to make decisions and predictions. A Data scientist primarily is Identifying new data sources. He then is engaged in collecting, correlating, and analyzing data across multiple data sources and developing data items and programming levels, along with applying the right kind of machine learning algorithms to get value out of the data. Top companies like Facebook, PayPal, eBay, Google, Amazon, Microsoft, Apple are looking for candidates available in the field of data science.
Data Science Course Learning Outcomes
The current marketplace is a data-driven environment and analyzing this data is one of the essential aspects that helps business leaders to make decisions based on facts, trends, and statistical numbers. Every industry is adopting cutting edge tools and technologies to analyze Big Data. This course gives you an overview of the key technologies involved in data science like machine learning, data mining, predictive modeling, visualization techniques, and statistics. This course takes you to step by step into the key skills and techniques needed to solve real-world business problems. One of the reasons why data science has fetched such popularity around the world is because it has the tools to crack customer behavior. So, one of the crucial areas that students will be exploring is learning the techniques to analyze customer sentiment and build models for Build prediction models for day-to-day applicability. Students will also gain expertise in Data Analytics, Data Wrangling, Descriptive and Predictive Analytics, Structured and Unstructured data, and will be able to communicate their findings effectively using Data Visualization techniques. With the completion of this course in Singapore, you will be able to market yourself in the fast-paced Data Science industry and display the various in-demand technical skills, as well as soft skills. You will also learn to:
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Who Should Sign Up?
- IT Engineers
- Data and Analytics Manager
- Business Analysts
- Data Engineers
- Banking and Finance Analysts
- Marketing Managers
- Supply Chain Professionals
- HR Managers
Data Science Course Modules
This module on Data Science will familiarize you with the principles of data analysis, statistics, and computing. The modules are well organized and give you a detailed overview of the comprehensive skill sets required in Data Science. The modules will introduce students to data cleansing, feature extraction, feature selection, regression techniques, hypothesis testing, text mining, NLP, forecasting, and black box technique. Students will develop programming skills and the ability to build and assess data-based models. With this course on Data Science from Singapore, students will get an opportunity to work with relevant datasets and apply the tools and techniques of data science to various industries and domains through working with hands-on projects that will help students to enhance their skills and also speed up their career.
Understand various data sources and why organizations are gearing up to store the data like never before. Learn on what are the various applications of data science in various industries ranging from FSI to LSHC to Retail and many more. Also one will appreciate the job opportunities in the space of data science, data modeling, and data analysis. Finally understand the golden rule on how to become a successful data scientist, data modeler, data analyst, etc.
Learn about the Project Management Methodology, CRISP-DM, for handling Data Science course projects & various concepts used in defining business problems & then performing data collection in line with business problems. Understand the importance of documenting the business objectives and business constraints so that the entire project is performed to solve business problems. Project charter overview will help participants understand the real-world documentation aspect as well.
Learn about data preparation and data cleansing in data science course projects to ensure that appropriate data is provided to the next step. Outlier analysis or treatment, handling missing values using imputation, transformation, normalization/standardization, etc., will be explained in thorough detail. Understand the various moments of a business decision and graphical representation so that structured descriptive analytics or descriptive statistics is performed. This exploratory data analytics is the first step in data analytics to draw meaningful insights.
Learn about applying domain knowledge to the data so that more meaningful variables are derived. Understand two main modules of feature engineering including feature extraction and feature selection. Knowing how to shortlist the critical inputs from trivial many inputs is the key to ensuring the high performance of the machine learning models. Understand about extracting features from structured as well as unstructured data such as videos, images, audio, textual files, etc.
Understand one of the key inferential statistical techniques called Hypothesis testing. Understand various parametric hypothesis tests. Learn about the implementation of a Regression method in data science course based on the business problems to be solved. Understand about Linear Regression as well as Logistic Regression techniques used to handle continuous as well as discrete output prediction. Evaluation techniques by understanding the measure of Error (RMSE), problems while building a Regression Model like Collinearity, Heteroscedasticity, overfitting, and Underfitting are explained in detail.
Understand the advanced regression models in data science course such as Poisson Regression, Negative Binomial Regression, Zero-Inflated models, etc., used to predict the count output variables. Learn about the various scenarios which trigger the application of advanced regression techniques. Understanding and evaluating the models using appropriate performance and accuracy measures of regression are explained in detail.
Data Mining branch called unsupervised learning is extremely important in solving problems, which require the application of only unsupervised learning tasks and also used to support predictive modeling. Clustering or segmentation has two prime techniques – K-Means clustering, as well as Hierarchical clustering and both, are explained in finer detail. Alongside, participants will also learn about handling datasets with large variables using dimension reduction techniques such as Principal Component Analysis or PCA. Finally one will learn about Association rules also called affinity analysis or market basket analysis or relationship mining.
The majority of unstructured data is in textual format and analyzing such data requires special techniques such as text mining or also called as text analytics. Techniques such as DTM/TDM using Term Frequency, Inverse Document Frequency, etc. are explained in this data science course module. One will also learn about generating a word cloud, performing sentiment analysis, etc. Also, advanced Natural Language Processing techniques such as LDA, topic mining, etc., are explained using practical use cases. Also, the learning includes extracting unstructured data from social media as well as varied websites.
A major branch of study in data science is Machine Learning also called Data Mining Supervised Learning or Predictive Modelling. One will learn about K Nearest Neighbors (KNN), Decision Tree (Boosting), Random Forest (Bagging), Stacking, Ensemble models and Naïve Bayes. One will learn about the various regularization techniques as well as understand how to evaluate for overfitting (variance) and underfitting (bias). All these are explained using industry relevant use cases and mini-projects.
Black box machine learning algorithms are extremely important in the field of machine learning. While there is no interpretation in the models, accuracy is unmatched in comparison to other shallow machine learning algorithms. Learn about the Perceptron algorithm and Multi-layered Perceptron algorithm or MLP. Understand about Kernel tricks used within Support Vector Machine algorithms. Understand about linearly separable boundaries as well as non-linear boundaries and now to solve these using Deep learning algorithms.
Understand the difference between cross-sectional data versus time series data. Search about the forecasting strategy employed in solving business problems. Understand various forecasting components such as Level, Trend, Seasonality & Noise. Also, learn about various error functions and which one is the best given a business scenario. Finally, build various forecasting models ranging from linear to exponential to additive seasonality to multiplicative seasonality.
Trends in Data Science
Which is the sexiest job of the 21st century? You got that right……. It’s a Data Scientist. Businesses have realized the power of data and are waking up to the wonders they can achieve with data science. Data science has given them a quick, cost-efficient, and innovative way to realize their business goals and connect insights to actions. The progress of technology has been amazingly fast-paced, and this has made it challenging to stay on top of all the latest trends. Emerging technologies are changing the way we interact with our environment or how businesses should effectively target their audience. The future trends will include cutting edge technologies like Artificial Intelligence, Machine Learning, IoT, Data Pipelines, etc. Given the complexity of the data landscape which is expected to expand to 176 zettabytes by 2025, the need for professionals who can juggle with epic data and identify, predict and plan strategies that can have a higher business impact is only going to rise.
We will see massive adoption of IoT devices along with analytics that will allow us to easily automate everyday tasks. Data pipelines when combined with AI, ML, and deep learning along with techniques such as graph analytics will play a key role in fueling digital transformation. Data Scientist is among the top five emerging jobs in Singapore and as the demand rises for digital talent big recognized firms such as Amazon, Google, Apple, etc. are looking for skilled professionals with the knowledge, skills, technology, and expertise in the field of Data Science. Join the course on Data science and move towards a successful career field that has a great number of job opportunities for you.
How We Prepare You
Additional Assignments of over 60-80 hours
Live Free Webinars
Resume and LinkedIn Review Sessions
3 Month Access to LMS
Job Assistance in Data Science 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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Data Science Course 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 sciences, 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 sciences, 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 at 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
Earn a certificate and demonstrate your commitment to the profession. Use it to distinguish yourself in the job market, get recognised at the workplace and boost your confidence. The Data Science Certificate is your passport to an accelerated career path.
**All certificate images are for illustrative purposes only. The actual certificate may be subject to change at the discretion of the Certification Body.
FAQs for Data Science Course
Different organisations use different terms for Data Professionals. You will sometimes find these terms being used interchangeably. Though there are no hard rules that distinguish one from another, you should get the role descriptions clarified before you join an organisation.
With growing demand, there is a scarcity of Data Science/Business Analytics professionals in the market. If you can demonstrate strong knowledge of Data Science concepts and algorithms, then there is a high chance for you to be able to make a career in this profession.
360DigiTMG provides internship opportunities through Innodatatics, our USA-based consulting partner, for deserving participants to help them gain real-life experience. This greatly helps students to bridge the gap between theory and practical.
There are plenty of jobs available for Data Professionals. Once you complete the training, assignments and the live projects, we will send your resume to the organisations with whom we have formal agreements on job placements.
We also conduct webinars to help you with your resume and job interviews. We cover all aspects of post-training activities that are required to get a successful placement.
While there are a number of roles pertaining to Data Professionals, most of the responsibilities overlap. However, the following are some basic job descriptions for each of these roles.
As a Data Analyst, you will be dealing with Data Cleansing, Exploratory Data Analysis and Data Visualisation, among other functions. The functions pertain more to the use and analysis of historical data for understanding the current state.
As a Data Scientist, you will be building algorithms to solve business problems using statistical tools such as Python, R, SAS, STATA, Matlab, Minitab, KNIME, Weka etc. A Data Scientist also performs predictive modelling to facilitate proactive decision-making.
A data engineer primarily does programming using Spark, Python, R etc. It often compliments the role of a Data Scientist.
A Data Architect has a much broader role that involves establishing the hardware and software infrastructure needed for an organisation to perform Data Analysis. They help in selecting the right Database, Servers, Network Architecture, GPUs, Cores, Memory, Hard disk etc.
After you have completed the data science course classroom sessions, you will receive assignments through the online Learning Management System that you can access at your convenience. You will need to complete the assignments in order to obtain your Data Scientist certificate.
In this blended programme, you will be attending 48 hours of classroom sessions over six days on campus in Kuala Lumpur, Malaysia. After completion, you will have access to the online Learning Management System for another three months for recorded videos and assignments. The total duration of assignments to be completed online is 40-60 hours. Besides this, you will be working on a live project for a month.
If you miss a class, we will arrange for a recording of the session. You can then access it through the online Learning Management System.
We assign mentors to each student in this programme. Additionally, during the mentorship session, if the mentor feels that you require additional assistance, you may be referred to another mentor or trainer.
No, the cost of the certificate is included in the programme package.
Jobs in Field of Data Science in Singapore
This training will give you the essential skills required to make a successful career in this field. Some of the distinguishable Data Scientist Job titles are Data Scientist, Data Engineer, Data Architect. Business Analyst, Data Analyst, Data Administrator, Business Intelligence Manager, etc..
Salaries in Singapore for Data Scientist
There are numerous job titles that Data Science technologies have generated which pay attractive salaries as compared to other IT jobs. A junior data scientist gets S$60,118, whereas a mid-level data scientist earns S$110,626, and a senior data scientist could earn S$141,783.
Data Science Projects in Singapore
Developing a voice bot, applying Deep Learning using simulation data to detect print quality artefacts, or developing an anomaly detector using machine learning algorithms to identify rare defects are some of the projects that you can take up to reach out to your potential employer.
Role of Open Source Tools in Analytics
Open source tools are important in the data science field. Some of the open-source tools we will be exploring in this course are R, Rstudio, and Python. These tools help in data mining, data manipulation, sentiment analysis, forecasting, manage workflows, debugging, etc.
Modes of Training for Data Science with Python
The course in Singapore is designed to suit the needs of students as well as working professionals. We at 360DigiTMG give our students the option of both classroom and online learning. We also support e-learning as part of our curriculum.
Industry Application of Data Science
Data Science is the new oil for all the industries of the world today. Its applications are diverse and enormous and are used in various sectors like healthcare, banking, finance, manufacturing, transport, e-commerce, education, etc.