Ranked #1 International Training Institute Rated 4.9/5 by 15k+ Students Learn Advance Machine Learning and GenerativeAI

Data Science and Artificial Intelligence

Embrace the future of Data Science and AI with this comprehensive data science course program, combining the best of both worlds: essential Data Science knowledge and in-demand Generative AI (Gen AI) skills. This data science course features special capstone projects, guest sessions from industry experts, masterclasses, and live BIA® DoubtBuster sessions.

Get hands-on experience with data science course including Python, Machine Learning, Deep Learning, Natural Language Processing (NLP), MLOps, Recurrent Neural Networks (RNNs), Generative Adversarial Networks (GANs), Attention, Transformers, BERT, and Business Intelligence Tools.

BIA® is highly rated at 4.9-star and is ranked #1 International Data Science Training Institute by British Columbia Times, Business World, Avalon Global and several recognized forums, making it a one-stop shop for mastering most sought-after skills and the latest AI technologies.

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Dual Certification: Data Science & Artificial Intelligence

The Two Most In-Demand and Highly Paid Skills

Ranked #1 International Training Institute

In 2023, by British Columbia Times, Business World & Others

3 Learning Paths

Data Science Certification (4 Months) | Data Science Diploma (6 Months) | Data Science Master Diploma (10 Months)

15000+ Learners

Data Science & AI Trained Students Across 105+ Campus in 7+ Countries

360° Career Support

Resume Building, Interview Prep, and Access to Partner Companies

Data Science and Artificial Intelligence Course Overview

Key Highlights

Immersive Data Science Course Training Classroom Experience

Hands-on Training By Industry Experts

15+ Industry Case Studies and Assignments

Data Science Course Modules Integrated with Generative AI

Exclusive Data Science Job Opportunities Portal

BIA® Alumni Status

Globally Recognized Dual Certification

Real World Projects and Case Studies

In-person Career Mentorship Sessions (1:1)

200+ Hours of Learning & Practical Exercises

360 Degree Career Support

Live Data Science Course BIA® DoubtBuster Sessions

350+ Corporate Partners

Immersive Plus Online Blended Learning

Practical Hands-on Capstone Projects

In-person Job Interview Preparation (1:1)

30+ Programming Tools & Technologies

Access to Top MNC Companies

No Cost EMI Options Available

BIA® Alumni Status

Syllabus for Data Science Course and Artificial Intelligence

Delve into 200+ hours of learning and hands-on exercises with our expertly crafted content. Our data science course modules are always up-to-date and seamlessly integrated with Generative AI. Developed by top industry experts, this data science course ensures a cutting-edge learning experience.

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Topics That Will Keep You Engaged and Curious

Python, Machine Learning, Deep Learning, Natural Language Processing (NLP), MLOps, Recurrent Neural Networks (RNNs), Generative Adversarial Networks (GANs), Attention, Transformers, BERT, and Business Intelligence Tools

Your Roadmap to Learning

Start with the basics, then move to advanced topics step by step. This prevents feeling overwhelmed and helps you remember and easily grasp new concepts. Each topic builds on what you’ve learned, forming a solid foundation for understanding more in data science course.

Ideal Candidates for Data Science Course

In the era of cutting-edge tools and AI, BIA’s data science course is open to everyone. Whether you’re a student pursuing Commerce, Arts, Banking, Engineering, or Science, you can dive into the world of data science. For professionals eyeing a shift into this field, this data science course is a great stepping stone. Business and IT professionals eager to boost their data skills will find valuable insights on this learning path.

Minimum Eligibility for Data Science Course

In today’s data science skill-based job market, degrees matter less than a passion for learning. Even a high school diploma is enough to kickstart this journey. Your love for data and enthusiasm for leveraging new-age technology will propel your career forward. Gain data science skills that not only open doors but also create new professional horizons.

Job Opportunities After Data Science Course

Data Scientist, Machine Learning Engineer, Deep Learning Engineer, Data Mining Specialist, AI/ML Model Validator, AI Research Scientist, Data Analyst, Data Visualization Specialist, AI Product Manager, AI Chatbot Designer, Big Data Engineer, AI Consultant, Quantitative Analyst, AIOPS Specialist, NLP Engineer, Computer Vision Engineer, Business Intelligence Analyst, Conversational AI Developer, Algorithm Developer, AI Solution Architect

Industries That Are Hiring Data Scientists and AI Specialists

The demand for Data Scientists and AI specialists spans across diverse sectors, including Technology, Finance, Banking, Healthcare, E-commerce, Retail, Telecom, Aerospace, Marketing, Entertainment, Sports and more, reflecting the broad applicability and impact of these technologies.

Globally Accredited Data Science Course in Mumbai – Andheri

Unlock the realm of Data Science with Boston Institute of Analytics’ premier Data Science course in Mumbai – Andheri, renowned as the most comprehensive data science training institute in India. Delve into the entire Data Science lifecycle, encompassing Data Collection, Extraction, Cleansing, Exploration, Transformation, and beyond. Explore a vast array of skills and tools, from Statistical Analysis to Text Mining, Regression Modeling to Deep Learning, all meticulously covered in our data science course curriculum in Mumbai – Andheri.
At Boston Institute of Analytics, we go beyond mere data science training – we offer a pathway to success. Join us in Mumbai – Andheri, and embark on a journey to become a sought-after Data Science professional in Mumbai – Andheri. Discover BIA is regarded as the best Data Science training institute in Mumbai – Andheri and beyond.

Why Should You Choose Boston Institute of Analytics For Data Science Course in Mumbai – Andheri?

Embark on your journey towards a rewarding career in Data Science with Boston Institute of Analytics, recognized as one of Mumbai – Andheri‘s premier data science training institutes. With a proven track record of shaping the careers of numerous Data Science professionals, both locally and internationally, we stand as a beacon of excellence in the field. Benefit from our expert trainers, each possessing over 15 years of professional experience in the industry. Our dual data science certification in Data Science & Data Analytics, widely regarded as the best in the industry, is tailored to equip you with the skills and knowledge needed to excel in the competitive landscape of Data Science in Mumbai – Andheri. At Boston Institute of Analytics, we offer a blended learning model that combines data science classroom sessions, instructor-led online sessions, and e-learning modules. Our dedicated data science placement cell and extensive network of 350+ corporate partners ensure that you receive ample opportunities for interviews and data science placement assistance. Whether you’re a seasoned professional looking to upskill or a fresh graduate aspiring to kickstart your data science career in Mumbai – Andheri, our comprehensive Data Science course in Mumbai – Andheri is designed to meet your needs and exceed your expectations. Join us today and take the first step towards unlocking your full potential in the dynamic field of Data Science in Mumbai – Andheri.

20+ Programming Tools, Libraries & Technologies Covered

10+ Generative AI Tools, Libraries & Technologies Covered

BIA® Dual Certification In Two Most In-Demand And Highly Paid Skills

Data Science

+

Artificial Intelligence

Explore our AI Powered Centralized Learning Hub

Our AI powered Learning Management System (LMS) is a centralized hub designed to enhance your data science training course experience. It provides seamless access to study materials, lecture recordings, personalized progress tracking, assignment submission, and automated grading. Additionally, it offers access to BIA® DoubtBuster to help clear any doubts you may have.

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Comprehensive Curriculum

Our data science course curriculum, meticulously crafted and delivered by Industry-Expert Trainers, offers a dynamic fusion of academic depth and real-world know-how.

Know Your Trainer

A seasoned pro in the very field you’re passionate about. Beyond learning, this is your golden ticket to tap into their years of hands-on expertise. See your trainers as more than a guide; envision them as a gateway to the industry you’re eager to join.

200+ Hours

Learning & Practicals

15+

Projects & Case Studies

30+

Tools & Technologies

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Data Science Course and AI Foundation: Orientation

Introduction to the Data Science Course
Importance of Data Science and AI

Fundamentals of Data Science
Introduction to Artificial Intelligence

Installing Anaconda
Setting up Jupyter Notebooks
Setting-up Power BI and Tableau Account
Introduction to Excel Environment

Overview of the Course Modules
Brief on Assignments and Assessments

Digital Platforms and Resources
Communication Channels

Mastering MS Excel

2 Quizzes

1 Project

Overview of Excel Interface
Key Formulas and Functions
Ranges and Tables
Data Cleaning – Text Functions, Dates and Times
Conditional Formatting
Sorting and Filtering

2 Quizzes

1 Project

Pivots
Data Analysis in Excel – Trends and Patterns
Data Visualization in Excel – Charts and Plots
Working With Multiple Worksheets
Linking and Referencing the Data Between Worksheets

Python for Data Science

2 Quizzes

1 Project

Overview of Python
Understanding Statements, Expressions and Indentation
Overview of Identifiers, Keywords and Comments
Variables: Declaration, Assignment and Naming Conventions
Common Data Types: Integers, Floats and Strings
Type Casting and Conversion
Operators in Python
Hands-on Activity

2 Quizzes

1 Project

Loop Control Statements: Break, Continue andPass
Defining and Calling Functions
Function Parameters and Return Values
Scope of Variables (Global and Local)
Advanced Functions
Default Values and Variable-Length Arguments
Recursive Functions
Map, Reduce and Filter
Introduction to Exceptions
Try, Except and Finally Blocks
Handling Common Errors
Hands-on Activity

2 Quizzes

1 Project

Basic Operations on Lists
Demonstration of List Manipulation Techniques
Slicing and Indexing in Lists
List Comprehension for Concise and Readable Code
Tuples Creation
Basic Operations on Tuples
Slicing And Indexing in Tuples
Common Operations on Both Lists and Tuples
Hands-on Activity

2 Quizzes

1 Project

Basic Operations on Dictionaries
Manipulating Dictionaries
Dictionary Comprehension for Concise Creation
Creation of Sets
Manipulating Sets
Common Operations on Both Dictionaries and Sets
Hands-on Activity

2 Quizzes

1 Project

Intro To Numpy and Creating Numpy Array
Basic Operations on Arrays
Indexing and Slicing
Reshaping, Stacking and Splitting
Iteration, Filtering and Boolean Indexing
Image Processing Using Numpy and Matplotlib
Hands-on Activity

2 Quizzes

1 Project

Data Structure in Pandas
Creating Dataframe and Loading Files
Data Exploration (EDA)
Creating and Saving Basic Plots Using Matplotlib
Creating Statistical Plots Using Seaborn
Exploring Relationships in Data: Pair Plot and Heat Map
Hands-on Activity

SQL for Data Science

2 Quizzes

1 Project

SQL and Its Significance
SQL’S Role in Data Retrieval and Manipulation
Select Statement for Data Retrieval
Retrieving Specific Columns and All Columns
Using Distinct to Remove Duplicates
Data Models & ER Diagrams
Relational Vs. Transactional Models
Organizing Data in Tables
Filtering Data with Where Clause
Sorting Data with Order By
Limiting Results with Limit
Using Aliases for Column Names
Hands-on Activity

2 Quizzes

1 Project

Creating and Using Temporary Tables
Adding Comments to SQL Code for Documentation
Introduction to Data Modeling
Designing A Database Schema
Sorting Data with Order By (Advanced)
Advanced Filtering (With In, Or, And, Not)
Performing Mathematical Operations on Data
Introduction to Aggregate Functions (Count, Sum, Avg, Max, Min)
Grouping Data with Group By
Filtering Grouped Data with Having
Understanding Subqueries and Their Types
Performing Join Operations (Inner Join, Left Join, Right Join, Full Outer Join)
Updating and Deleting Data with SQL
Analyzing Data with Statistics
Hands-on Activity

Application of Statistics and Probability

2 Quizzes

1 Project

Define Statistics and Its Importance
Explain The Types of Data: Categorical and Numerical
Inferential and Descriptive Statistics
Measure Of Central Tendency: Mean, Median, Mode
Measure Of Dispersion: Variance and Standard Deviation
Probability Basics, It’s Rules and Notation
Probability Distribution – Discrete and Continuous
Normal Distribution and Properties
Central Limit Theorem and Its Importance
Skewness and T-Distributions

2 Quizzes

1 Project

Hypothesis Testing – Null and Alternative
Significance Level (Alpha) and P-Value
One-Sample and Two-Sample T-Test
Visualization Plots for Data Exploration
Interpretation of Visualization
Correlation and Regression
Confidence Interval
Hypothesis Testing With Z-Test
Chi-Square Test for Categorical Data
One-Way and Two-Way Anova

Explore Supervised Machine Learning

2 Quizzes

1 Project

Intro to ML & Its Role in Data Analysis
Types of Machine Learning – Supervised, Unsupervised and Reinforcement
Data Pre-processing Methods
Feature Scaling
Linear Regression as Regression Technique
Simple Linear Regression
Hands-on Activity

2 Quizzes

1 Project

Model Evaluation Metrics for Regression
Mean Absolute Error (MAE)
Mean Squared Error (MSE)
Root Mean Squared Error (RMSE)
R-Squared (Coefficient of Determination)
Multiple Linear Regression
California Housing Dataset – Model Evaluation
Hands-on Activity

2 Quizzes

1 Project

Overview of Logistic Regression
Binary Classification Problem and Logit Function and Odds Ratio
Binary & Multi-class LR
Classification Matrix: Accuracy, Precision, Recall and F1-Score
Confusion Matrix Interpretation
ROC Curves & AUC
Hands-on Activity

2 Quizzes

1 Project

Decision Tree and Its Structure
Decision Nodes and Leaf Nodes, Parent/Child Node
Splitting Criteria – Gini Impurity and Entropy
Tree Pruning and Overfitting
Techniques to Prevent Overfitting
Random Forest – Ensemble Learning and Bagging
Gradient Boosting And AdaBoost Ensemble Method
Hands-on Activity

2 Quizzes

1 Project

K-Fold Cross-Validation for Model Evaluation
Hyper-parameter Tuning Using Grid Search
Detailed Coverage of Classification Metrics
Precision, Recall, F1-Score, ROC Curves, AUC
Interpretation and Practical Usage
Hands-on Activity

Explore Unsupervised Machine Learning

2 Quizzes

1 Project

K-Means Clustering and Its Applications
K-Means Algorithm
Choosing the Number of Clusters (K)
Introduction to Hierarchical Clustering
Agglomerative Hierarchical Clustering
Hands-on Activity

2 Quizzes

1 Project

Classification and Regression with SVM
The Concept of Margin and Support Vectors
Kernel Trick for Non-Linear Data
Introduction to KNN
Predictions of KNN Based on Nearest Neighbors
Euclidean Distance, Manhattan Distance and Other Distance Metrics
Choosing the Value of K
Hands-on Activity

2 Quizzes

1 Project

Understanding Time Series Data
ARIMA Model and Its Components
Building ARIMA Models
Forecasting with ARIMA
Seasonal ARIMA (SARIMA) Model and Its Components
Building and Forecasting with SARIMA
Model Evaluation and Tuning
Hands-on Activity

Explore Deep Learning

2 Quizzes

1 Project

Overview of Artificial Neural Networks (ANNs)
Neural Network Basics
Model Representation in Deep Learning
Deep Learning Applications
Training Deep Learning Models
Building A Simple Artificial Neural Network
Hands-on Activity: ANN
Convolutional Neural Networks (CNNs)
Hands-on Activity: CNN

2 Quizzes

1 Project

Recurrent Neural Networks (RNNs)
Recurrent Neurons
Vanishing Gradient Problem
LSTM and GRU
Building and Training RNN
Overfitting and Regularization Techniques
Dropout and Normalization
Model Evaluation, Metrics and Hyper-parameter Techniques
Hands-on Activity: RNN, LSTM, GRU

Discover Natural Language Processing (NLP)

2 Quizzes

1 Project

Overview of NLP
Challenges in NLP
Key NLP Tasks
Text Preprocessing in NLP
NLP Libraries and Frameworks
Feature Extraction and Representation
Building A Text Classification Model
Hands-on Activity

2 Quizzes

1 Project

Advanced Word Embeddings
GLOVE (Global Vectors for Word Representation)
N-Grams
Recurrent Neural Networks (RNN)
Long Short-Term Memory (LSTM)
GRU
Hands-on Activity

Class Project: Application of ML, Deep Learning and NLP

2 Quizzes

1 Project

Introduction – Data Science Workflow
Data Collection
Exploratory Data Analysis (EDA) and Visualization
Data Preprocessing
Machine Learning Model Development
Introduction to Model Deployment
Model Deployment Using Streamlit

2 Quizzes

1 Project

Introduction to Problem Statement
Dataset Overview
NLP Model Development
Deep Learning Model Development
Model Evaluation
Model Deployment Using Streamlit

Mastering Data Visualization

2 Quizzes

1 Project

Introduction to Power BI, Key Features, Installation and Setup
Understanding the Power BI Desktop Interface
Exploring the Workspace: Ribbons, Panes and Menus
Data Transformation
Data Modeling: Relationships, Keys and Hierarchies
Data Analysis Expressions (DAX), DAX Functions and Calculations
Advanced DAX Calculations: Time Intelligence, Filters and Measures
Charts and Page Layouts
Creating A Power BI Dashboard
Publishing and Sharing Reports and Dashboards
Hands-on Activity

2 Quizzes

1 Project

Overview of Tableau Prep
Data Connections, Cleaning and Transformation
Introduction to Tableau Desktop
Data Source Connection and Navigation
Visual Analytics – Sorting and Filtering Data Interactivity
Working with Calculated Fields
Aggregations and Level of Detail (LOD) Expressions
Creating Charts and Dashboards in Tableau
Hands-on Activity

Mastery in Generative AI (Gen AI)

2 Quizzes

1 Project

Overview of Generative AI
Definition and Key Features of Generative Models
Applications of Generative AI Across Various Industries
Ethical Considerations and Potential Biases in Generative AI
Architecture Overview: Transformers and Their Key Components
Pre-Training and Fine-Tuning of LLMs
Comparison of Different LLM Models (GPT-3, T5, Jurassic-1 Jumbo)
Introduction to Hugging Face and Text Generation/Summarization
Setting Up the Environment and Accessing Hugging Face
Exploring Pre-Trained LLM Models and Functionalities
Implementing Text Generation Tasks Using Transformers and LLMs
Experimenting With Text Summarization Techniques with LLMs
Analyzing the Strengths and Limitations of Different Approaches
Hands-on Activity

2 Quizzes

1 Project

Fine-Tuning LLMs for Specific Tasks
Dataset Preparation and Pre-Processing Techniques
Fine-Tuning Hyper-parameter Optimization
Evaluating the Performance of Fine-Tuned Models (Bleu and Rouge)
Introduction to Retrieve, Augment and Generate (RAG) for Fine-Tuning
Hands-On: Fine-Tuning A LLM with Custom Data
Selection of LLM Models and Dataset
Fine-Tuning with Hugging Face Libraries
Evaluating and Analyzing the Fine-Tuned Model’s Performance
Comparison of Results with The Pre-Trained Model
Hands-on Activity

2 Quizzes

1 Project

Advanced Fine-Tuning Techniques
Prompt Engineering and Its Impact on Generated Text
Exploring Techniques Like Beam Search and Nucleus Sampling
Conditional Text Generation Based on Specific Contexts
Text-To-Speech and Speech-To-Text Integration with Hugging Face
Model Evaluation Techniques
Going Beyond Bleu and Rouge: Exploring Advanced Metrics for Different Tasks
Qualitative Analysis of Generated Text and Summarization Outputs
Importance of Human Evaluation in Generative Models
Hands-on: Fine-Tuning with Advanced Techniques and Text-To-Speech/Speech-To-Text
Experimenting with Prompt Engineering and Advanced Generation Techniques
Implementing Conditional Text Generation Based on Specific Contexts
Integrating Text-To-Speech and Speech-To-Text Functionalities
Evaluating the Performance of Fine-Tuned Models Using Advanced Metrics

2 Quizzes

1 Project

Real-World Applications of Generative AI
Case Studies of Successful LLM Applications in Various Industries
Identifying New Opportunities for Generative AI Solutions
Ethical Considerations and Responsible Deployment Practices
Designing and Developing a Chatbot
Defining the Chatbot’s Functionalities and Target Audience
Integrating Fine-Tuned LLM Models for Text Generation, Dialogue, and Text-To-Speech/Speech-To-Text
Building the Chatbot Interface and User Interaction Flow
Implementing and Deploying the Chatbot With Gradio
Testing and Evaluating the Chatbot

Capstone Project

2 Quizzes

2 Project

Project and Dataset Assignment by Capstone Mentor
Orientation Session by Capstone Mentor – Project Expectations
Mentorship Session by Capstone Mentor – Doubt Resolutions
Project Presentation

Career Enhancement

Presentation Skills
Email Etiquettes
LinkedIn Profile Building
Personality Development and Grooming

Interview Do’s and Don’ts
Mock Interviews
HR And Technical Interview Prep
One-On-One Feedback

Learn Through Industry Projects in Data Science Course and AI

Highlighting a selection of real-world projects and case studies supported by leading companies across industries

CO2 Emission Prediction in Automobiles

Building a model to predict Toyota vehicle CO2 emissions using fuel data for sustainable innovation.

Predictive Analysis for E-Commerce Success

Crafting a predictive system to forecast customer behavior using diverse ML algorithms for strategic insights.

Advanced Phishing Detection

Developing a system to detect phishing attempts with advanced ML algorithms for enhanced cybersecurity measures.

Decoding Public Sentiment

Crafting sentiment analysis, leveraging advanced ML and NLP for deep insights into user sentiments and behaviors.

Predicting Amazon Book Genres

Forecasting book genres from text data using advance NLP techniques and Machine Learning algorithms.

Visualizing Entertainment in Tableau

Explore Netflix’s global content with Tableau: map, top genres, titles added yearly, and interactive details.

Forecasting Trends in Banking and Finance

Predict future stock prices with precision using ARIMA, analyzing history to unveil strategic financial patterns.

Precise Pneumonia Detection

Automate pneumonia detection in chest X-rays using CNN, optimizing healthcare workflows, and aiding diagnostics.

Developing a GenAI Chatbot

Embark on a culinary adventure with a GPT-powered chatbot, guiding users to master delightful recipes.

The BIA® Advantage

Blended Learning Opportunities

BIA®’s blended learning experience enables students to choose between lively data science course IN-CLASSROOM sessions or seamlessly attend the same session ONLINE.
Our In-Classroom data science course sessions are Live Streamed, allowing students to join in ONLINE mode with real-time options to interact with the trainer and fellow classmates.

Flipped Classroom Learning

Our flipped classroom learning model empowers students to review instructional materials online before class, fostering active discussions, problem-solving, and hands-on activities during face-to-face sessions.

Asynchronous Learning Modules

Elevate in-person data science course learning with our asynchronous modules, featuring quizzes, assignments, lecture recordings, and extra resources. This allows students to revise learning materials at their own pace and according to their preferences.

Industry Experience

Faculty members with significant industry experience bring practical insights and real-world knowledge into the classroom, enhancing the relevance of the data science course curriculum