United States

Professional Program in Data Science

The online Advanced program in Data Science offered by learningsaint lets you gain proficiency in data science. You will work on real-world projects in data science with R, hadoop dev, admin, test and analysis, apache spark, scala, deep learning, SQL, mongoDB, and more. Upon successfully completing the program, you will be awarded PLA credits by Belhaven University that can be applied to Belhaven University degree programs.

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Upskill for Your Dream Job

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Students Placed

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Highest Salary

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Average Salary Hike

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Join The Best Data Science And Analytics Course

Learn the real-world application of data science and build analytical models that enhance business outcomes. This job-assurance program is ideal for recent graduates and professionals who want to develop a successful data science and analytics career. You will gain practical knowledge about the implications of data science and analytics in real-world businesses and prepare to work as a data science professional in an emerging field of data science and analytics.

Job Assurance

Our program comes with a job assurance that offers you a chance to be placed at over 500 top-tier partner organisations hiring machine learning and artificial intelligence professionals.

Dedicated Career Services

Our career services include resume development, profile enhancement, career mentorship, job assurance workshops and one-on-one career counselling to ensure you land the right job.

Real-world Projects

Implement what you’ve learned with over 25 real-world projects and case studies specially formulated by industry experts to make you job-ready.

Job-specific Curriculum

Learn the practical applications of data science, Python, SQL, data analytics, power BI, and tableau while gaining expertise in these subjects.

Live Learning Module

Our expert faculty delivers our robust curriculum using an interactive module and hands-on training methods to prepare you to work in various data science roles.

KPMG India COE Organised Hackathons

Make your resume stand out by participating in coding hackathons to tackle complex business problems and get an opportunity to compete in a national-level competition.

Trusted By Millions Of Learners Around The World

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About the Program

This Advanced program offers 10 courses and 30 industry-based projects with 1 capstone project. As a part of the training, you will receive five additional self-paced courses co-created with IBM. Additionally, you will also get exclusive access to IBM Watson Cloud Lab for Chatbots course.

Key Highlights

232 Hrs Instructor-led Training
253 Hrs Projects and Exercises
Flexible Schedule
Mentor Support
PLA Credits from Belhaven University
104 Hrs Self-paced Videos
Job Assistance
Lifetime Free Upgrade
One-on-one with Industry Mentors

Advanced Program in Data Science Course Curriculum

Python for Data Science

Module 01 – Introduction to Data Science using Python
Module 02 – Python basic constructs
Module 03 – Maths for DS-Statistics & Probability
Module 04 – OOPs in Python (Self-paced)
Module 05 – NumPy for mathematical computing
Module 06 – SciPy for scientific computing
Module 07 – Data manipulation
Module 08 – Data visualization with Matplotlib
Module 09 – Machine Learning using Python
Module 10 – Supervised learning
Module 11 – Unsupervised Learning
Module 12 – Python integration with Spark (Self-paced)
Module 13 – Dimensionality Reduction
Module 14 – Time Series Forecasting

Machine Learning

Module 01 – Introduction to Machine Learning
Module 02 – Supervised Learning and Linear Regression
Module 03 – Classification and Logistic Regression
Module 04 – Decision Tree and Random Forest
Module 05 – Naïve Bayes and Support Vector Machine (self-paced)
Module 06 – Unsupervised Learning
Module 07 – Natural Language Processing and Text Mining (self-paced)
Module 08 – Introduction to Deep Learning
Module 09 – Time Series Analysis (Self-paced)

AI & Deep Learning

Module 01 – Introduction to Deep Learning and Neural Networks
Module 02 – Multi-layered Neural Networks
Module 03 – Artificial Neural Networks and Various Methods
Module 04 – Deep Learning Libraries
Module 05 – Keras API
Module 06 – TFLearn API for TensorFlow
Module 07 – DNNs (deep neural networks)
Module 08 – CNNs (convolutional neural networks)
Module 09 – RNNs (recurrent neural networks)
Module 10 – Gpu in deep learning
Module 11 – Autoencoders and Restricted Boltzmann Machine (RBM)
Module 12 – Deep learning applications
Module 13 – Chatbots

Data Visualization with Power BI

Module 01 – Introduction to Power BI
Module 02 – Data Extraction
Module 03 – Data Transformation – Shaping & Combining Data
Module 04 – Data Modelling & DAX
Module 05 – Data Visualization with analytics
Module 06 – Power BI Service (Cloud), Q&A, and Data Insights
Module 07 – Power BI Settings, Administration & Direct Connectivity
Module 08 – Embedded Power BI with API & Power BI
Module 09 – Power BI Advance & Power BI Premium

MongoDB

Module 01 – Introduction to NoSQL and MongoDB
Module 02 – MongoDB Installation
Module 03 – Importance of NoSQL
Module 04 – CRUD Operations
Module 05 – Data Modeling and Schema Design
Module 06 – Data Management and Administration
Module 07 – Data Indexing and Aggregation
Module 08 – MongoDB Security
Module 09 – Working with Unstructured Data

MS-SQL

Module 01 – Introduction to SQL
Module 02 – Database Normalization and Entity-Relationship Model
Module 03 – SQL Operators
Module 04 – Working with SQL: Join, Tables, and Variables
Module 05 – Deep Dive into SQL Functions
Module 06 – Working with Subqueries
Module 07 – SQL Views, Functions, and Stored Procedures
Module 08 – Deep Dive into User-defined Functions
Module 09 – SQL Optimization and Performance
Module 10 – Advanced Topics
Module 11 – Managing Database Concurrency
Module 12 – Programming Databases Using Transact-SQL
Module 13 – Microsoft Courses: Study Material

Data Science with R

Module 01 – Introduction to Data Science with R
Module 02 – Data Exploration
Module 03 – Data Manipulation
Module 04 – Data Visualization
Module 05 – Introduction to Statistics
Module 06 – Machine Learning
Module 07 – Logistic Regression
Module 08 – Decision Trees and Random Forest
Module 09 – Unsupervised Learning
Module 10 – Association Rule Mining and Recommendation Engines
Module 11 – Introduction to Artificial Intelligence
Module 12 – Time Series Analysis
Module 13 – Support Vector Machine (SVM)
Module 14 – Naïve Bayes
Module 15 – Text Mining

Who Can Apply for the Course?

Individuals with a bachelor’s degree and a keen interest to learn AI and Data Science
IT professionals looking for a career transition as Data Scientists and Artificial Intelligence Engineers
Professionals aiming to move ahead in their IT career
Artificial Intelligence and Business Intelligence professionals
Developers and Project Managers
Freshers who aspire to build their career in the field of Artificial Intelligence and Data Science

What roles can a person trained in Data Science & Artificial Intelligence play?

Senior Data Scientist

Understand the issues and create models based on the data gathered, and also manage a team of data scientists.

AI Expert

Build strategies on frameworks and technologies to develop AI solutions and help the organization prosper.

Machine Learning Expert

With the help of several machine learning tools and technologies, build statistical models with huge chunks of business data.

Applied Scientist

Design and build machine learning models to derive intelligence for the numerous services and products offered by the organization.

Big Data Specialist

Create and manage pluggable service-based frameworks that are customized in order to import, cleanse, transform, and validate data.

Senior Business Analyst

Extract data from the respective sources to perform business analysis, and generate reports, dashboards, and metrics to monitor the company’s performance.

Skills to Master

Python

Data Science

Data Analysis

GIT

MLOps

Data Wrangling

SQL

Story Telling

Machine Learning

Prediction algorithms

NLP

PySpark

Model

Data visualization

Tools to Master

Languages and Tools Covered

Specializations & Electives Overview

Banking, Finance, & Insurance: Dive into projects like Churn Analysis, Risk-Reward Assessment, Stock Market Analysis, and Fraud Detection to grasp fundamental concepts in BFSI.

Ecommerce & Marketing: Explore Customer Lifetime Analysis, Ad Campaign Evaluation, Market Basket Analysis, and Dynamic Pricing strategies in this field.

Healthcare & Pharmacy: Explore Payer and Provider Analytics, as well as Analytics applied in the Pharmaceutical Industry to gain insights into essential Healthcare principles.

HR & Operations: Engage in Attrition Analysis, Promotion Assessment, Productivity Evaluation, and Resource Optimization to comprehend core BFSI principles in a different context.

Participate in Weekday Problem-Solving Sessions led by Industry Experts

Engage in problem-solving sessions guided by industry professionals throughout the weekdays.

Enhance problem-solving skills through active participation on platforms like HackerRank and HackerEarth.

Acquire daily insights into new problem-solving techniques and strategies.

Access personalized doubt resolution sessions whenever needed to ensure continual learning and growth.

Alumni Highlights

200+

Global Companies
$122K PA

Average CTC
$250K PA

Highest CTC
87%

Average Salary Hike

Top Data Science Case Studies for Learning Saint

Estimating Credit Risk through Data Analysis and Visualization

Analysing Banking Dataset: This case study involves utilizing Data Analysis and Visualization techniques on a banking dataset to assess the Credit Risk associated with individual borrowers. By conducting this study, the aim is to assist the bank in evaluating and managing the risk linked to its loan borrowers.

Data Cleansing and Enrichment for a Job Portal:

Enhancing a Job Portal Dataset: This case study focuses on Data Cleansing and Processing for a large-scale Job Portal Dataset. The objective is to prepare the data for further analysis and machine learning model training. The outcome aims to empower the job portal with clean, enriched data for informed decision-making and implementation of various AI algorithms to gain profound insights.

Evaluating Dimensionality Reduction Techniques in Healthcare Data:

Assessing Dimensionality Reduction: This case study involves the comparison of various Dimensionality Reduction methods using a high-dimensional Healthcare Dataset. The goal is to apply different algorithms to evaluate information loss in each case. This study aims to determine the effectiveness of Dimensionality Reduction techniques and their applicability in managing high-dimensional data in healthcare analysis.

By the end of this program, you'll achieve

Comprehensive comprehension of diverse data types and datasets.

Proficiency in extracting insights and patterns from raw data of varied forms.

Proficient creation of visualizations and dashboards to drive data-driven decision-making processes.

Great Understanding of Structured and Unstructured Databases

Thorough understanding of both structured and unstructured databases.

Ability to conduct multifaceted analyses on a wide array of data categories.

In-depth knowledge of Machine Learning and Deep Learning algorithms.

Capability to craft robust predictive models employing advanced Machine Learning and Deep Learning techniques.

Profound understanding of NLP (Natural Language Processing) and Time Series concepts.

Data Science Batch Profile

Career Support and Mentorship

Receive personalized feedback on weekly assignments and case studies from leading industry and subject matter experts.

Engage in multiple mock interviews conducted by Kaggle Grandmasters and seasoned Data Scientists representing startups.

Benefit from lifelong access to the Learningsaint Learning Portal, ongoing support from the Learningsaint Alumni Network, and dedicated placement services.

Participate in over 20 guided industry projects and case studies led by domain and subject matter experts, providing a step-by-step learning experience.

Access the Learning Saint Learning Portal for a lifetime, along with continuous support from the Learning Saint Alumni Network and placement services.

Let’s Learn Together

The Learning Saint Advantage

Individualised Support and Direction

1:1 Free Unlimited Doubt clearing sessions
1:1 Student support
Challenges during hackathons to hone your talents
E-portfolio to display your skills
1:1 Personality development classes

Get Ready with Domain Experts

Learn from top Data Scientist Educators from the Country through a Live Online classroom.
24X7 Support from Teaching Assistants for Help in Assignments, Discussions, and Doubts Resolutions.

Industry Leaders for Professional Grooming

Know what’s Happening inside the industry, and What’s really required to make it through by engaging with Data Scientist
Accompany them with sessions on Hiring, Day-to-Day Life of a Data Scientists etc.

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"I'm amazed by the hands-on experience I've gained during my time here. The labs, projects, and research opportunities have given me a deep understanding of engineering principles. The diverse community of students also made my college life unforgettable."

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