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iHUB-IIT-R

Data Science Course in Manila

93,702 Ratings

  • Data Science Course with placement assistance in Manila
  • Offered by iHUB, an innovation hub of IIT Roorkee
  • Two days of campus immersion at IIT Roorkee included
  • Learn various tools and techniques to excel in Data Science training in Manila

Ranked #1 Data Science Course by India TV

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Data Scientist Course Key Highlights

50+ Live sessions across 7 months
218 Hrs Self-paced Videos
200 Hrs Project & Exercises
Learn from IIT Roorkee Faculty and Industry Practitioners
1:1 with Industry Mentors and 24*7 Support
Resume Preparation and LinkedIn Profile Review
Campus Immersion at IIT Roorkee
No-cost EMI Option
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Trustpilot 3109
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Data Science Training Overview

Why should you take up the Data Scientist course in Manila?

  • As per Glassdoor, the average income of Data Scientists in India is about ₹976k per annum
  • LinkedIn has over 3,000 Data Science job opportunities in India
  • Data Scientist is the best job of the 21st century – Harvard Business Review
  • The global Big Data market to reach US$122 billion in revenue in 6 years – Frost & Sullivan
  • The number of jobs for all the US data professionals will increase to 2.7 million per year – IBM

Today, almost all industry verticals, regardless of their customer orientation, are actively hiring Data Scientists, which makes it truly worthwhile to get certified.

According to Glassdoor, the average income of a Data Scientist in Manila is ₹10Lakhs per year.

Top companies that hire Data Scientists are:

  • Fidelity Investments
  • Accenture
  • Aon
  • Oath
  • MSD
  • Intel
  • Amazon
  • Google

Intellipaat’s online Data Science training course is exclusively designed by industry experts for

  • BI Professionals and Analysts
  • Big Data Experts
  • Big Data Statisticians
  • Machine Learning Professionals
  • Information Architects and Predictive Analytics Experts
  • Freshers or Professionals looking for a Data Science career

On average, a Data Scientist earns around ₹1,000,000/year, which is almost 20 percent more than the national average. One of the top five skills that pay the most in the domain includes

  • Machine Learning – ₹1,050,000/year
  • Python – ₹980,000/year
  • R – ₹985,000/year
  • Data Analysis – ₹983,000/year
  • Statistical Analysis – ₹1,100,000/year

Some of the top employers hiring professionals in this domain are Mu Sigma, Amazon, EY, IBM, Accenture, Flipkart, Robert Bosch, etc. Also, the city, often called the Silicon Valley of India, is home to thousands of startups that are actively looking for certified professionals.

In this course, we have included real-world industry-based projects, which help you gain hands-on experience in the field and prepare you for challenging roles.

Industry Project Name Objective
BFSI Fraud Detection in Banking System Deploying Data Science to detect fraudulent activities and take remedial actions
Entertainment Movie Recommendation Engine Building a movie recommendation engine, based on user interests
E-commerce Making Sense of Customer Buying Patterns Deploying target selling to customers

Intellipaat is a premier online coaching institute that offers the best Data Science courses in Manila, which help you master concepts such as

  1. Data analysis, project life cycle, and Data Science in the real world
  2. Machine Learning algorithms
  3. Techniques of evaluation, experimentation, and project deployment
  4. Analysis segmentation using clustering and the technique of prediction
  5. Python with Data Science
  6. Git, Storytelling
  7. Data Science at scale with PySpark, AI with TensorFlow
  8. Deploying Machine Learning models on Clouds ( MLOps)
  9. Data visualization with Tableau
  10. Natural Language Processing and its applications
  11. Microsoft excel for data analysis and data transformation
  12. Data Science projects, analytics, and recommender systems
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Talk To Us

We are happy to help you 24/7

With data collection, ‘the sooner, the better’ is the best answer. - The CEO of Yahoo
Everything is going to be connected with data and mediated by software - The CEO of Microsoft
The world is now awash in data, and we can see consumers more cleanly - The Co-founder of PayPal

Career Transition

55% Average Salary Hike

$1,20,000 The Highest Salary

12000+ Career Transitions

500+ Hiring Partners

Career Transition Handbook

*Past record is no guarantee of future job prospects

Meet the Data Science Mentors

Who can apply for the Data Scientist course?

  • Information Architects and Statisticians
  • Developers looking to master Machine Learning and Predictive Analytics
  • Big Data, Business Analysis, Business Intelligence, and Software Engineering Professionals
  • Aspirants who are looking to work as Machine Learning Experts, Data Scientists, etc.
  • Anyone who wants to learn machine learning, artificial intelligence, data visualization, data analytics, data structures, and algorithms (DSA).
who-can-apply

What roles does a Data Scientist play?

Data Scientist

Design and implement scalable codes alongside effectively developing high-quality applications.

Analytics and Insights Analyst

Develop solutions for fixing quality issues in the data upon investigating the reported errors in the data.

AI & ML Engineer

Use Lambda functions and API Gateway to integrate machine learning models into web apps and deploy models in SageMaker.

Data Engineer & Data Analyst

Perform data cleansing, and data transformation, analyze the outcomes, and present the insights in reports and dashboards.

Junior Data Scientist

Analyze the operating behavior using advanced statistical techniques and tools. Also, create algorithms with prescriptive and descriptive methods.

Applied Scientist

Derive intelligence for business products through designing and developing machine learning models.

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Skills Covered

Python

SQL

Mathematical Modelling

Data Science

Descriptive Statistics

Inferential Statistics

Data Analysis

Machine Learning

Generative AI

Prompt Engineering

ChatGPT

Artificial Intelligence

Large Learning Models

Supervised & Unsupervised Learning

MLOps

Story Telling

Data Visualization

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Tools Covered

pyspark python jupyter Scipy numpy pandas matplotlib tensorflow SQL tableau excel git SparkSQL
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Course Fees

Online Classroom Preferred

  • Live Classes from IIT Faculty & Industry Experts
  • Certification from iHUB IIT Roorkee
  • Career Services (Mock Interviews, Resume Preparation)
  • Placement Assistance upon clearing PRT
  • Dedicated Learning Manager
16 Jul

TUE - FRI

07:00 AM TO 09:00 AM IST (GMT +5:30)

20 Jul

SAT - SUN

10:00 AM TO 01:00 PM IST (GMT +5:30)

20 Jul

SAT - SUN

08:00 PM TO 11:00 PM IST (GMT +5:30)

$1,492 10% OFF Expires in

Corporate Training

  • Customized Learning
  • Enterprise Grade Learning Management System (LMS)
  • 24x7 Support
  • Enterprise Grade Reporting

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Data Scientist Training Curriculum

Live Course Self Paced Industry Expert Academic Faculty

Module 1 – Preparatory Session - Linux and Python

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Python 

  • Introduction to Python and IDEs – The basics of the Python programming language, how you can use various IDEs for python development like Jupyter, Pycharm, etc. 
  • Python Basics – Variables, Data Types, Loops, Conditional Statements, functions, decorators, lambda functions, file handling, exception handling ,etc.
  • Object Oriented Programming – Introduction to OOPs concepts like classes, objects, inheritance, abstraction, polymorphism, encapsulation, etc.
  • Hands-on Sessions And Assignments for Practice – The culmination of all the above concepts with real-world problem statements for better understanding. 

Linux

  • Introduction to Linux  – Establishing the fundamental knowledge of how Linux works and how you can begin with Linux OS. 
  • Linux Basics – File Handling, data extraction, etc.
  • Hands-on Sessions And Assignments for Practice – Strategically curated problem statements for you to start with Linux. 
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Module 2 – Data Wrangling with SQL

Preview

SQL Basics – 

  • Fundamentals of Structured Query Language
  • SQL Tables, Joins, Variables 

Advanced SQL –  

  • SQL Functions, Subqueries, Rules, Views
  • Nested Queries, string functions, pattern matching
  • Mathematical functions, Date-time functions, etc. 

Deep Dive into User Defined Functions

  • Types of UDFs, Inline table value, multi-statement table. 
  • Stored procedures, rank function, SQL ROLLUP, etc.

SQL Optimization and Performance

  • Record grouping, searching, sorting, etc. 
  • Clustered indexes, common table expressions.

Hands-on exercise: 

Writing comparison data between the past year and the present year with respect to top products, ignoring the redundant/junk data, identifying the meaningful data,  and identifying the demand in the future(using complex subqueries, functions, pattern matching concepts).

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Extract Transform Load

  • Interacting with APIs

Data Handling with NumPy

  • NumPy Arrays, CRUD Operations, etc.
  • Linear Algebra – Matrix multiplication, CRUD operations, Inverse, Transpose, Rank, Determinant of a matrix, Scalars, Vectors, Matrices.

Data Manipulation Using Pandas

  • Loading the data, data frames, series, CRUD operations, splitting the data, etc.

Data Preprocessing

  • Exploratory Data Analysis, Feature engineering, Feature scaling, Normalization, standardization, etc.
  • Null Value Imputations, Outliers Analysis and Handling, VIF, Bias-variance trade-off, cross-validation techniques, train-test split, etc.

Data Visualization

  • Bar charts, scatter plots, count plots, line plots, pie charts, donut charts, etc. with Python matplotlib.
  • Regression plots, categorical plots, area plots, etc, with Python seaborn.
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Descriptive Statistics – 

  • Measure of central tendency, the measure of spread, five points summary, etc. 

Probability 

  • Probability Distributions, Bayes’ theorem, central limit theorem. 

Inferential Statistics –  

  • Correlation, covariance, confidence intervals, hypothesis testing, F-test, Z-test, t-test, ANOVA, chi-square test, etc.
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Introduction to Machine Learning 

  • Supervised, Unsupervised Learning.
  • Introduction to scikit-learn, Keras, etc.

Regression 

  • Introduction classification problems, Identification of a regression problem, dependent and independent variables.
  • How to train the model in a regression problem.
  • How to evaluate the model for a regression problem.
  • How to optimize the efficiency of the regression model.

Classification 

  • Introduction to classification problems, Identification of a classification problem, and dependent and independent variables.
  • How to train the model in a classification problem.
  • How to evaluate the model for a classification problem.
  • How to optimize the efficiency of the classification model.

Clustering 

  • Introduction to clustering problems, Identification of a clustering problem, dependent and independent variables.
  • How to train the model in a clustering problem.
  • How to evaluate the model for a clustering problem.
  • How to optimize the efficiency of the clustering model.
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  • Linear Regression – Creating linear regression models for linear data using statistical tests, data preprocessing, standardization, normalization, etc.
  • Logistic Regression – Creating logistic regression models for classification problems – such as if a person is diabetic or not, if there will be rain or not, etc.
  • Decision Tree – Creating decision tree models on classification problems in a tree like format with optimal solutions.
  • Random Forest – Creating random forest models for classification problems in a supervised learning approach.
  • Support Vector Machine – SVM or support vector machines for regression and classification problems.
  • Gradient Descent – Gradient descent algorithm that is an iterative optimization approach to finding the local minimum and maximum of a given function.
  • K-Nearest Neighbors – A simple algorithm that can be used for classification problems.
  • Time Series Forecasting – Making use of time series data, gathering insights and useful forecasting solutions using time series forecasting.
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  • K-means – The k-means algorithm that can be used for clustering problems in an unsupervised learning approach.
  • Dimensionality reduction – Handling multi dimensional data and standardizing the features for easier computation.
  • Linear Discriminant Analysis –  LDA or linear discriminant analysis to reduce or optimize the dimensions in the multidimensional data.
  • Principal Component Analysis – PCA follows the same approach in handling the multidimensional data.

Performance Metrics

  • Classification reports – To evaluate the model on various metrics like recall, precision, f-support, etc.
  • Confusion matrix – To evaluate the true positive/negative, and false positive/negative outcomes in the model.
  • r2, adjusted r2, mean squared error, etc.
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Artificial Intelligence Basics 

  • Introduction to keras API and TensorFlow

Neural Networks

  • Neural networks
  • Multi-layered Neural Networks
  • Artificial Neural Networks 

Deep Learning 

  • Introduction to Deep Learning (by Academic Faculty)
  • Deep neural networks
  • Convolutional Neural Networks 
  • Recurrent Neural Networks
  • GPU in deep learning
  • Autoencoders, restricted boltzmann machine 
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The Data Science capstone project focuses on establishing a strong hold of analyzing a problem and coming up with solutions based on insights from the data analysis perspective. The capstone project will help you master the following verticals: 

  • Extracting, loading and transforming data into usable format to gather insights. 
  • Data manipulation and handling to pre-process the data.
  • Feature engineering and scaling the data for various problem statements. 
  • Model selection and model building on various classification, regression problems using supervised/unsupervised machine learning algorithms.
  • Assessment and monitoring of the model created using the machine learning models.
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  • Recommendation Engine – The case study will guide you through various processes and techniques in machine learning to build a recommendation engine that can be used for movie recommendations, restaurant recommendations, book recommendations, etc.
  • Rating Predictions – This text classification and sentiment analysis case study will guide you towards working with text data and building efficient machine learning models that can predict ratings, sentiments, etc.
  • Census – Using predictive modeling techniques on the census data, you will be able to create actionable insights for a given population and create machine learning models that will predict or classify various features like total population, user income, etc.
  • Housing – This real estate case study will guide you towards real world problems, where a culmination of multiple features will guide you towards creating a predictive model to predict housing prices.
  • Object Detection – A much more advanced yet simple case study that will guide you toward making a machine learning model that can detect objects in real-time.
  • Stock Market Analysis – Using historical stock market data, you will learn about how feature engineering and feature selection can provide you with some really helpful and actionable insights for specific stocks.
  • Banking Problem – A classification problem that predicts consumer behavior based on various features using machine learning models.
  • AI Chatbot – Using the NLTK python library, you will be able to apply machine learning algorithms and create an AI chatbot.
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  • LSTM – What is LSTM?, How does LSTM work, Applications of LSTM, etc.
  • Transformers – What are transformers, how does a transformer work in deep learning, applications of transformers, types of transformers, encoder-decoded, self-attention, etc.
  • BERT – Language Models, What is BERT, How does BERT work, how is BERT different from LSTM, applications of BERT, etc.
  • GPT – What are generative pre-trained models (GPT), how does a GPT work?, real life examples of GPT, etc.
  • LLM – NLP and Language models, what are LLMs, how does a LLM work, applications of LLM, etc.
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Elective

Power BI Basics

  • Introduction to Power BI, Use cases and BI Tools , Data Warehousing, Power BI components, Power BI Desktop, workflows and reports , Data Extraction with Power BI.
  • SaaS Connectors, Working with Azure SQL database, Python and R with Power BI
  • Power Query Editor, Advance Editor, Query Dependency Editor, Data Transformations, Shaping and Combining Data ,M Query and Hierarchies in Power BI.

DAX 

  • Data Modeling and DAX, Time Intelligence Functions, DAX Advanced Features

Data Visualization with Analytics  

  • Slicers, filters, Drill Down Reports
  • Power BI Query, Q & A and Data Insights
  • Power BI Settings, Administration and Direct Connectivity
  • Embedded Power BI API and Power BI Mobile
  • Power BI Advance and Power BI Premium

Hands-on Exercise:

Creating a dashboard to depict actionable insights in sales data.

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Introduction to MLOps 

  • MLOps lifecycle
  • MLOps pipeline 
  • MLOps Components, Processes, etc

Deploying Machine Learning Models 

  • Introduction to Azure Machine Learning 
  • Deploying Machine Learning Models using Azure
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Version Control 

  • What is version control, types, SVN.

GIT

  • Git Lifecycle, Common Git commands, Working with branches in Git
  • Github collaboration (pull request), Github Authentication (ssh and Http)
  • Merging branches, Resolving merge conflicts, Git workflow
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  • Job Search Strategy
  • Resume Building
  • Linkedin Profile Creation
  • Interview Preparation Sessions by Industry Experts
  • Mock Interviews
  • Placement opportunities with 400+ hiring partners upon clearing the Placement Readiness Test.
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Excel Fundamentals 

  • Reading the Data, Referencing in formulae , Name Range, Logical Functions, Conditional Formatting, Advanced Validation, Dynamic Tables in Excel, Sorting and Filtering 
  • Working with Charts in Excel, Pivot Table, Dashboards, Data And File Security 
  • VBA Macros, Ranges and Worksheet in VBA 
  • IF conditions, loops, Debugging, etc.

Excel For Data Analytics 

  • Handling Text Data, Splitting, combining, data imputation on text data, Working with Dates in Excel, Data Conversion, Handling Missing Values, Data Cleaning, Working with Tables in Excel, etc.  

Data Visualization with Excel

  • Charts, Pie charts, Scatter and bubble charts
  • Bar charts, Column charts, Line charts, Maps
  • Multiples: A set of charts with the same axes, Matrices, Cards, Tiles

Excel Power Tools 

  • Power Pivot, Power Query and Power View

Classification Problems using Excel

  • Binary Classification Problems, Confusion Matrix, AUC and ROC curve 
  • Multiple Classification Problems  

Information Measure in Excel

  • Probability, Entropy, Dependence 
  • Mutual Information 

Regression Problems Using Excel

  • Standardization, Normalization, Probability Distributions 
  • Inferential Statistics, Hypothesis Testing, ANOVA, Covariance, Correlation
  • Linear Regression, Logistic Regression, Error in regression, Information Gain using Regression

Hands-on Exercise:

Classification problem using excel on sales data, and statistical tests on various samples from the population.

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Data Science Projects

Career Services

Career Services
resume

Career Oriented Sessions

Throughout the course

Over 10+ live interactive sessions with an industry expert to gain knowledge and experience on how to build skills that are expected by hiring managers. These will be guided sessions that will help you stay on track with your up upskilling.

linkedin

Resume & LinkedIn Profile Building

After 70% of course completion

Get assistance in creating a world-class resume & LinkedIn profile from our career services team and learn how to grab the attention of the hiring manager at the profile shortlisting stage

interview

Mock Interview Preparation

After 80% of the course completion.

Students will go through a number of mock interviews conducted by technical experts who will then offer tips and constructive feedback for reference and improvement.

expert

1 on 1 Career Mentoring Sessions

After 90% of the course completion

Attend one-on-one sessions with career mentors on how to develop the required skills and attitude to secure a dream job based on a learner’s educational background, past experience, and future career aspirations.

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Placement Assistance

Upon movement to the Placement Pool

Placement opportunities are provided once the learner is moved to the placement pool upon clearing Placement Readiness Test (PRT)

job_portal

Exclusive access to Intellipaat Job portal

After 80% of the course completion

Exclusive access to our dedicated job portal and apply for jobs. More than 400 hiring partners’ including top start-ups and product companies hiring our learners. Mentored support on job search and relevant jobs for your career growth.

Advance Data Science Certification

Advanced-Certification-in-Data-Science-and-AI Click to Zoom

The Data Science courses offered aim to upskill millions of students and professionals in trending technologies through a blend of theoretical and hands-on knowledge and are taught by leading academicians.

Upon completion of this data science course in Manila, you will:

  • Receive an Advanced Certification in Data Science and AI from iHUB IIT Roorkee ( An Innovation Hub of IIT Roorkee). Receive live lectures from IIT Faculty & Industry Experts

Key achievements of IIT Roorkee:

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Data Science Training FAQs

Why should I learn Data Science in Manila from Intellipaat?

Intellipaat offers exclusive Data Science courses in Manila for professionals who want to expand their knowledge base and start a career in this field. There are many reasons for choosing Intellipaat:

  • A personal mentor to track your progress
  • Immersive online instructor-led sessions conducted by SMEs
  • Extensive LMS, allowing you to view recorded sessions within 3 hours
  • Real-time exercises, assignments, and projects
  • 24/7 learning support
  • A Large community of like-minded learners
  • Industry-recognized Intellipaat badge
  • Personalized job support

Please understand that Intellipaat does not directly forward resumes to companies or recruiters. However, we provide a dedicated placement team that conducts mock interviews and works with you to refine your resume. Our objective is to enhance your readiness for job interviews and facilitate your entry into the Data Science job market.

Our online training is carefully crafted by leading Data Scientists from India and the United States. These experts have structured the course to make it accessible, even if you come from a non-technical background or have limited prior knowledge. Additionally, we offer hands-on practice with real-world projects, ensuring that newcomers can comfortably grasp the concepts.

At Intellipaat, our career mentoring session connects you with Data Science professionals who are ready to address your concerns about career pathways and the potential for progression in this sector.

Intellipaat provides different group discounts and special deals for our online training, depending on the size and type of your group. To find out more about these discounts and how they work, please connect with our course advisors who will furnish you with all the relevant information.

For Intellipaat courses, geographical boundaries do not apply. It does not matter in whichever area of Manila you are you can access our online course sitting at home or office.

We provide training in two categories:

  • Self-paced training
  • Online classroom training

The cost of the self-paced training mode is ₹15,048, and the online classroom training mode costs ₹22,743.

No Cost EMI options are available. For more detailed information, contact our team @ IN: +91-7022374614

Intellipaat is the leading course provider in Manila. Our e-learning institute provides top courses in Data Analytics Course, Artificial Intelligence, Machine Learning, R programming language, Python Certification, Python for Data Science, Business Analytics, and others to help you gain full control of your Data Science career path.

To learn Data Science for free, you need to look at the blogs and YouTube videos published by Intellipaat. Read the top-recommended blogs on their Interview Questions, Tutorial, and everything about Data Science.

If you’re interested in joining our Data Scientist training in Manila, the first step is to select either online instructor-led training or self-paced training. Once you’ve made your choice, you can complete your payment using a major credit card, debit card, or EMI option.

Intellipaat selects subject matter experts from top MNCs, who have at least 8 to 12 years of experience in the domain, as instructors. They are qualified Data Science instructors and are selected after going through our rigorous selection process and proving their capabilities.

Intellipaat’s teaching assistants are subject matter experts (SMEs) with the primary goal of helping you achieve professional certification in your chosen field. Our trainers provide interactive video lectures to cover the latest industry technologies and enrich your learning through hands-on projects. Please remember that our teaching assistance is accessible during regular hours.

This online course comprises all the topics that are required and significant to learn so that you can master this technology. This Data Science course comprises both basic and advanced-level concepts involved in this technology so that you can learn them and master the skills to pursue a career in this domain. Moreover, the trainers of this course are experts in the domain who spend time and effort to teach you all the concepts in detail.

The world of Data Science, with components such as Machine Learning, Deep Learning, and Artificial Intelligence, may initially appear complex. However, our online training, led by IIT Roorkee faculty and experienced industry professionals, simplifies these concepts by using real-world examples for better comprehension.

Intellipaat is one of the most affordable e-learning providers today. This Data Science online training in Manila costs ₹85,044.

No Cost EMI options are available. For more detailed information, contact our team @ IN: +91-7022374614

At Intellipaat, you can enroll in either the instructor-led online training or self-paced training. Apart from this, Intellipaat also offers corporate training for organizations to upskill their workforce. All trainers at Intellipaat have 12+ years of relevant industry experience, and they have been actively working as consultants in the same domain, which has made them subject matter experts. Go through the sample videos to check the quality of our trainers.

Intellipaat is offering you the most updated, relevant, and high-value real-world projects as part of the training program. This way, you can implement the learning that you have acquired in real-world industry setup. All training comes with multiple projects that thoroughly test your skills, learning, and practical knowledge, making you completely industry-ready.

You will work on highly exciting projects in the domains of high technology, ecommerce, marketing, sales, networking, banking, insurance, etc. After completing the projects successfully, your skills will be equal to 6 months of rigorous industry experience.

You can definitely make the switch from self-paced training to online instructor-led training by simply paying the extra amount. You can join the very next batch, which will be duly notified to you.

Upon successful completion of Intellipaat’s training program, which encompasses real-world projects, quizzes, and assignments, and achieving a minimum score of 60 percent in the qualifying exam, you will be granted Intellipaat’s course completion certificate. This certificate holds significant value in organizations associated with Intellipaat, including more than 80 leading multinational corporations globally and a range of Fortune 500 enterprises.

Intellipaat offers query resolution, and you can raise a ticket with the dedicated support team at any time. You can avail yourself of email support for all your queries. We can also arrange one-on-one sessions with our support team If your query does not get resolved through email. However, 1:1 session support is given for 6 months from the start date of your course.

Intellipaat provides placement assistance to all learners who have completed the training and moved to the placement pool after clearing the PRT (Placement Readiness Test). More than 500+ top MNCs and startups hire Intellipaat learners. Our alumni work with Google, Microsoft, Amazon, Sony, Ericsson, TCS, Mu Sigma, etc.

Apparently, no. Our job assistance is aimed at helping you land your dream job. It offers a potential opportunity for you to explore various competitive openings in the corporate world and find a well-paid job, matching your profile. The final hiring decision will always be based on your performance in the interview and the requirements of the recruiter.

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