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.

Upskill for Your Dream Job

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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.

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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.

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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.

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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.

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Job-specific Curriculum

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

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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.

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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.

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Trusted By Millions Of Learners Around The World

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
  • 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
  • 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)
  • 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
  • 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
  • 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
  • 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
  • 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
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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
who can apply

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

AI

GIT

MLOps

Data Wrangling

SQL

Story Telling

Machine Learning

Prediction algorithms

NLP

PySpark

Model

Data visualization

Tools to Master

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Languages and Tools Covered

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Specializations & Electives Overview

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Banking, Finance, & Insurance: Dive into projects like Churn Analysis, Risk-Reward Assessment, Stock Market Analysis, and Fraud Detection to grasp fundamental concepts in BFSI.
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Ecommerce & Marketing: Explore Customer Lifetime Analysis, Ad Campaign Evaluation, Market Basket Analysis, and Dynamic Pricing strategies in this field.
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Healthcare & Pharmacy: Explore Payer and Provider Analytics, as well as Analytics applied in the Pharmaceutical Industry to gain insights into essential Healthcare principles.
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HR & Operations: Engage in Attrition Analysis, Promotion Assessment, Productivity Evaluation, and Resource Optimization to comprehend core BFSI principles in a different context.
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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.
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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.

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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.
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Data Science Batch Profile

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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.
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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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Get Every General Answers From Here

Learning management system, combines a wide range of features to present a class setting without having the students come into a physical classroom. It all depends on the WordPress LMS plugin you go with, but in general.
Learning management system, combines a wide range of features to present a class setting without having the students come into a physical classroom. It all depends on the WordPress LMS plugin you go with, but in general.
Learning management system, combines a wide range of features to present a class setting without having the students come into a physical classroom. It all depends on the WordPress LMS plugin you go with, but in general.
Learning management system, combines a wide range of features to present a class setting without having the students come into a physical classroom. It all depends on the WordPress LMS plugin you go with, but in general.
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"I can't express how much I've benefited from the courses here. The professors are not just knowledgeable but also incredibly supportive. The practical approach to learning has prepared me for the real world, and I'm now working at my dream tech company."

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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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