Learn from Home Offer
Data Scientist Course in Philippines (85 Courses, 67+ Projects)
85 Online Courses
67 Hands-on Projects
660+ Hours
Verifiable Certificate of Completion
Lifetime Access
Python Data Scientist Courses (18 Courses)
Python Data Scientist Projects (6 Projects)
R Programming Data Scientist Courses (12 Courses)
R Programming Data Scientist Projects (11 Projects)
SAS Data Scientist Courses (9 Courses)
* One Time Payment & Get Lifetime Access
What you get in this Data Scientist Course in Philippines?
Online Classes
Technical Support
Mobile App Access
Case Studies
About Data Scientist Course Philippines
Course | No. of Hours | |
---|---|---|
Machine Learning with Python 2022 | 5h 15m | |
Project on Machine Learning - Covid19 Mask Detector | 2h 05m | |
Machine Learning Project - Auto Image Captioning for Social Media | 2h 23m | |
Machine Learning with SciKit-Learn in Python | 8h 37m | |
Machine Learning Python Case Study - Predictive Modeling | 8h 27m | |
Matplotlib for Python Developers - Beginners | 4h 12m | |
Matplotlib for Python Developers - Intermediate | 2h 52m | |
Matplotlib for Python Developers - Advanced | 6h 37m | |
Pandas with Python Tutorial | 5h 47m | |
NumPy and Pandas Python | 5h 01m | |
Pandas Python Case Study - Data Management for Retail Dataset | 3h 28m | |
Python Case Study - Sentiment Analysis | 1h 06m | |
Data Science with Python | 4h 14m | |
Artificial Intelligence with Python - Beginner Level | 2h 49m | |
Artificial Intelligence with Python - Intermediate Level | 4h 36m | |
AI Artificial Intelligence with Python | 6h 15m | |
Video Analytics using OpenCV and Python Shells | 2h 13m | |
Machine Learning using Python | 3h 26m | |
Statistics Essentials with Python | 3h 23m | |
Project on Tensorflow - Implementing Linear Model with Python | 1h 46m | |
Project - Data Analytics with Data Exploration Case Study | 5h 7m | |
Project on ML - Random Forest Algorithm | 1h 29m | |
Seaborn Python - Beginners | 2h 28m | |
Seaborn Python - Intermediate | 1h 18m | |
Seaborn Python - Advanced | 1h 56m | |
PySpark Python - Beginners | 2h 3m | |
PySpark Python - Intermediate | 2h 05m | |
PySpark Python - Advanced | 1h 14m | |
Machine Learning Python Case Study - Diabetes Prediction | 1h 03m | |
R Studio UI and R Script Basics | 4h 9m | |
R Programming for Data Science | A Complete Courses to Learn | 5h 7m | |
R Practical - Logistic Regression with R | 4h 18m | |
Project - Decision Tree Modeling using R | 1h 44m | |
Project on ML - Churn Prediction Model using R Studio | 1h 22m | |
Financial Analytics in R - Beginners | 3h 5m | |
Financial Analytics in R - Intermediate | 1h 28m | |
Financial Analytics in R - Advanced | 1h 35m | |
R for Finance - Beginners to Beyond | 2h 17m | |
Comprehensive Course on R | 3h 54m | |
Project on R - Forecasting using R | 4h 34m | |
Project - Fraud Analytics using R & Microsoft Excel | 2h 34m | |
Project - Marketing Analytics using R and Microsoft Excel | 2h 9m | |
Machine Learning with R | 20h 28m | |
Case Study - Customer Analytics using Tableau and R | 2h 7m | |
Case Study - Pricing Analytics using Tableau and R | 2h 39m | |
Business Analytics using R - Hands-on! | 16h 21m | |
Project - Market Basket Analysis in R | 37m | |
Project - Hypothesis Testing using R | 3h 6m | |
Data Visualization with R Shiny - The Fundamentals | 39m | |
Data Science with R | 6h 2m | |
R Studio Anova Techniques Course | 2h 18m | |
SAS Business Analytics for Beginners | 10h 42m | |
Predictive Modeling with SAS Enterprise Miner | 9h 21m | |
Quantitative Finance with SAS | 3h 29m | |
SAS Statistics | 8h 18m | |
SAS ODS (Output Delivery System) | 9h 08m | |
SAS PROC SQL | 13h 49m | |
SAS Macros | 7h 38m | |
SAS Advanced Analytics | 12h 34m | |
SAS Graph | 2h 1m | |
SAS DS2 | 5h 2m | |
SAS SQL | 3h 03m | |
SAS Practical - Macros | 5h 12m | |
SAS Advanced Programming | 11h 24m | |
SAS Categorical Data Analysis | 7h 26m | |
Certified SAS Base Programmer | 12h 2m | |
SAS Features for Starters | 1h 5m | |
SAS PROC SQL Features | 1h 53m | |
Big Data and Hadoop Training | Online Hadoop Course | 2h 3m | |
Hadoop Architecture and HDFS | 6h 13m | |
MapReduce - Beginners | 3h 34m | |
MapReduce - Advanced | 5h 35m | |
Hive - Beginners | 2h 47m | |
Hive - Advanced | 5h 11m | |
PIG - Beginners | 2h 1m | |
PIG - Advanced | 2h 13m | |
NoSQL Fundamentals | 2h 01m | |
Mahout | 3h 51m | |
Apache Oozie | 2h 13m | |
Apache Storm | 2h 4m | |
Apache Spark - Beginners | 1h 5m | |
Apache Spark - Advanced | 6h 14m | |
Splunk Fundamentals | 8h 33m | |
Splunk Advanced 01 - Knowledge Objects | 9h 29m | |
Splunk Advanced 02 - Administration | 39h | |
Project on Hadoop - Sales Data Analysis | 47m | |
Project on Hadoop - Tourism Survey Analysis | 53m | |
Project on Hadoop - Faculty Data Management | 35m | |
Project on Hadoop - E-Commerce Sales Analysis | 35m | |
Project on Hadoop - Salary Analysis | 49m | |
Project on Hadoop - Health Survey Analysis using HDFS | 56m | |
Project on Hadoop - Traffic Violation Analysis | 1h 25m | |
Project on Hadoop - Analyze Loan Dataset using PIG/MapReduce | 2h 33m | |
Project on Hadoop - Case Study on Telecom Industry using HIVE | 2h 2m | |
Project on Hadoop - Customers Complaints Analysis using HIVE/MapReduce | 53m | |
Project on Hadoop - Social Media Analysis using HIVE/PIG/MapReduce/Sqoop | 3h 34m | |
Project on Hadoop - Sensor Data Analysis using HIVE/PIG | 5h 26m | |
Project on Hadoop - Youtube Data Analysis using PIG/MapReduce | 3h 02m | |
Hadoop and HDFS Fundamentals on Cloudera | 1h 22m | |
Project on Hadoop - Log Data Analysis | 1h 32m | |
SPSS 2022 - Beginners | 1h 05m | |
SPSS 2022 - Advanced | 5h 22m | |
Advanced SPSS Project: Impact of EMI on Home Loan | 43m | |
Advanced SPSS Project: Impact of Total Turnover in Equity Market | 58m | |
Advanced SPSS Project: Impact of Trade Data in Equity Market | 46m | |
SPSS GUI and Applications | 1h 13m | |
SPSS - Correlation Techniques | 1h 8m | |
SPSS - Linear Regression Modeling | 3h 08m | |
SPSS - Multiple Regression Modeling | 2h 34m | |
SPSS - Logistic Regression | 2h 01m | |
SPSS - Multinomial Regression | 2h 2m | |
SPSS GUI for Statistical Analysis | 2h | |
Tableau Desktop Training 2022 | 4h 17m | |
Tableau Project-Creating Dashboard and Stories For Financial Markets | 2h 08m | |
Tableau Project - Russo-Ukraine War A Data Analytical Review | 1h 02m | |
Tableau | 4h 7m | |
BI Tools and Tableau Analytics | 5h 38m | |
Business Intelligence with Tableau | 5h 43m | |
Tableau Features Hands-on! | 5h 32m | |
Tableau Practical - Super Store Business Requirements | 45m | |
Analytics using Tableau | 9h 29m | |
Minitab for Beginners - 2022 | 1h 12m | |
Advanced Minitab Training - 2022 | 4h 39m | |
Minitab Practical - Impact of Predictors on Response | 1h 36m | |
Statistical Analysis using Minitab - Beginners to Beyond | 4h 27m | |
Minitab GUI and Descriptive Statistics | 2h 43m | |
ANOVA in Minitab | 53m | |
Correlation Techniques in Minitab | 2h 21m | |
Project on Minitab - Regression Modeling | 9h 54m | |
Minitab Predictive Modeling using Excel | 55m | |
MATLAB - Beginners | 2h 58m | |
MATLAB - Intermediate | 47m | |
MATLAB - Advanced | 4h 1m | |
Oracle SQL | 17h 32m | |
Oracle PLSQL | 13h 2m | |
Oracle DATABASE Admin DBA 1 Course | 9h 27m | |
Machine Learning with Tensorflow | 13h 29m | |
Hands-on Deep Learning Training | 10h 8m | |
Project - Exploratory Data Analysis EDA using ggplot2, R and Linear Regression | 2h 07m | |
Project on R - HR Attrition and Analytics | 2h 43m | |
Logistic Regression using SAS Stat | 4h 28m | |
Linear Regression in Python | 2h 28m | |
Python Data Science Case Study - Predicting Survival of Titanic Passengers | 2h 6m | |
Project on R - Card Purchase Prediction | 2h 28m | |
Machine Learning Python Case Study - Develop Movie Recommendation Engine | 51m | |
R Practical - Employee Attrition Prediction using Random Forest Technique and R | 1h 6m | |
Project on Term Deposit Prediction using Logistic Regression CART Algorithm | 1h 38m | |
Poisson Regression with SAS Stat | 2h 22m | |
Machine Learning Project using Caret in R | 1h 58m | |
Time Series Analysis in Python - Sales Forecasting | 2h 12m |
Course Name | Online Data Scientist Course Philippines |
Deal | You get access to all videos for the lifetime |
Hours | 660+ Video Hours |
Core Coverage | You get to learn data science using R, Python, Machine Learning, Artificial Intelligence, Big data & Hadoop, Predictive Modeling, Business Analytics, Data Visualization, and other areas under Data Science. |
Course Validity | Lifetime Access |
Eligibility | Anyone serious about learning data science and wants to make a career in analytics |
Pre-Requisites | Basic knowledge of data and analytics |
What do you get? | Certificate of Completion for the course |
Certification Type | Course Completion Certificates |
Verifiable Certificates? | Yes, you get verifiable certificates for each85 course, 67 Projects with a unique link. These link can be included in your resume/Linkedin profile to showcase your enhanced skills |
Type of Training | Video Course – Self Paced Learning |
Software Required | None |
System Requirement | 1 GB RAM or higher |
Other Requirement | Speaker / Headphone |
Data Scientist Course in Philippines Curriculum
Due to the vastness of the application of the Data Science domain, the tools and technologies available to aid are also expanding at a rapid pace. It could prove to be intimidating to a fellow aspirer unless a structured guide or path is available. This Data Scientist Course in the Philippines was created as a one-stop solution to build a strong fundamental base, both in the technology and science (or theory) required to be efficient while practicing Data Science. It thus starts with getting a rock-solid foundation in python programming and it’s most powerful libraries for Data Science. Next, it gets you familiar with R, language designed primarily for data science and analysis. Once these languages are picked up, the course continues to explore more complex and niche technologies, which can reduce significant programming effort during some part of your data science project life cycle. These include SAS, Hadoop, SPSS, Splunk, MATLAB, Minitab, Tableau, and Oracle DB. Each of these enables one or more features among data storage, data processing at scale, exploratory data analysis, structured data processing, and data visualization capabilities, etc. Technology training, together with the multiple hands-on projects you stumble upon during coursework, will show real-life problems faced during a data science project and provide crucial experience to overcome inertia, not addressed in most of the available online courses. Post-certification, a person should be confident to take on real-life problems at scale independently.
Data Scientist Course – Certificate of Completion
Who is a Data Scientist?
A necessary skill for any professional to be called a Data Scientist is understanding of mathematical and statistical algorithms and formulae required to identify and prove statistical relationships between events. This forms the actual foundation of any reasoning to be done for a given problem statement.
Once a person has good enough capability to understand how to prove the existence of statistical relations (or non-existent of one), he/she attempts to do it as a scale.
This is done with the aid of modern technologies to mainly automate data collection, data cleaning and wrangling, data storage, data visualization, statistical inference and proof, and then prediction capability, and optimizing data pipelines for production usage. Most junior data scientist become efficient at 1-2 of these activities, experience has a fair idea of all, and the veteran is capable of causing advancements in a given area.
Industry Growth Trend
The overall data science platform market is expected to grow from USD 19.58 billion in 2016 to USD 101.37 billion by 2021, at a CAGR of 38.9% from 2016 to 2021.[Source - MarketsandMarkets]
Average Salary
[Source - Indeed]
Which Skills will you learn in this Course?
The Data Scientist Course in the Philippines covers a wide set of technologies, ensuring a one-stop solution for all your data science needs. It begins with a deep-diving in python usage, a skill you must have. Then moves to teach R, a language at par with python for data science and analysis. These two are the foundational skills for any exploratory projects. The second half of the courses get you familiar with key technologies considered cutting edge in the industry currently. These include Hadoop, SAS, Tableau, Splunk, Minitab, etc. Each of the sections comes with hands-on projects and exercises giving you the necessary experience in their usage.
Pre-requisites
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- The Data Scientist Course in the Philippines is self-contained and can be picked up even by a person completely new to the field of programming and data science. It is designed as an all-rounder course of the field, thus doesn’t necessarily require any pre-known skill, and will require a machine to work upon and an internet connection to follow through the coursework.
Nonetheless, learning time can be reduced significantly if there’s previous programming or scripting experience, especially familiarity with languages R or Python.
Target Audience
- Data Scientist Course in the Philippines in itself contains content that addresses the basics or the foundational details and as well as advanced problems and an experienced professional also might not have encountered. Thus it is limited to the will for the person to grow holistically in this futuristic field. College students, fresh graduates and experienced candidates can all find the content useful in their growth.
Data Scientist Course Philippines – FAQ’s
Why should you take up the Data Scientist course in the Philippines?
The Philippines, being one of prominent developing countries, experienced massive development and growth in tech-based industries including e-commerce and digital media usage. In the past decade, roles related to SEO and Digital Marketing picked up traction, creating thousands of new jobs for skilled workers. Big Data and Data Analytics domain is the focus now, and there’s already an ever-growing demand for skilled Data Science professionals. A person can create great demand for the next decade why undergoing complete professional training, such as the one taught here.
What is the Data Scientist market trend in the Philippines?
While there’s already a global shortage of skilled Data Scientists, this demand is extremely high in developing countries like the Philippines due to budding start-up industries. Also, the country is assumed to be the center for big data analytics in the future. Recently even the government voiced their prediction of increasing demand for skilled professionals in the analytics domain, proving it’s vitality both in the short and long term. The industry is on the verge of exploding in terms of shortage of resources and now is the right time to enter this domain with a long term growth perspective.
Sample Preview
Career Benefits
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- Successful
- command strong knowledge in core theory revolving around statistical inference, understand the different rules and hypotheses to apply a varying set of problem statements, and wield the technology-stack required to do these activities within a feasible and acceptable time of an enterprise. Any personnel finishing the course in its entirety will possess a strong control over all these activities. One would be able to pick up large-scale industrial analytics projects and do anything required to turn around new projects efficiently and effectively.
Reviews
Data science with python
The course goes through the different areas of data science with python. Besides a fundamental theory regarding the explained concepts, the diverse concepts are exemplified with short python programs. The lessons are good to understand and the programs presented to illustrate and implement the concepts are simple and significant.
Linked
Jorge Giro
Business Analytics using R
The data scientist course was very comprehensive and covered in detail the business analytics using R. The tutor used clear English and explained very carefully the different topics of the course. It is very rare to find a course online that covers that much information going from the basics of statistics to the application of R to business analytics. I think this is a competitive advantage of the course since the majority of this kind of courses available online are made for people who already know statistics or even some knowledge about the software itself, but this Data scientist course tried to cover them all which made very comfortable for me as a student.
Linked
Abderrahmane Friha
Amazing First Sashay with Customer Analytics
If you’re looking to dipping your toes into customer analytics, this Data scientist course is a good first start. It provides the foundation knowledge for customer analytics from mapping out the customer lifecycle and drilling down on what needs to be down per phase of the said lifecycle. I need to note that the data scientist training course explains from a bank / financial service standpoint, though this I feel allows the course to explain the concepts better instead of not having any examples at all.
Linked
Acee Vitangcol
Great content
Amazing material put together, it goes in-depth with functions on Excel, R, and SAS. I like the complexity and the level of knowledge especially the Excel area. If you are looking to analyze data regularly using excel 2010, or similar platforms such as R, this training is full of great content at a very high level.
Linked
Jorge Dominguez
Good Introduction to Marketing Analytics
It is a good Introduction to Marketing Analytics. It lists the typical activities carried out in the practice of predictive analytics. Furthermore, it helps to define how to make analytics more efficient, lists the type of models that are used in marketing and digital marketing, and some hints on the leading vendors of predictive analytics.
Linked
Ricardo Garibay-Martínez