Best Data Science Course in Mumbai
AI Driven hands-on interactive data science classes in Mumbai with real-time data science projects. Learn from working IT professionals with 16+ years of experience AI tools, AI automation technologies.
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Best Data Science Course in Mumbai with Certification & Placement Support
The demand for skilled data professionals is increasing daily in these fields like banking, healthcare, retail, e-commerce, manufacturing, finance, and IT. Organizations depend on data to understand customers, improve data operations, identify opportunities, and make informed business decisions.
If you are looking for a Data Science Course in Mumbai that combines practical learning with industry-relevant skills, Technogeeks offers a structured training program for students, graduates, and working professionals.
If your goal is to pursue a Masters in Data Science, transition into a data-focused career, or wants to increase your existing technical skills, the course provides hands-on learning and industry-oriented training.
Why Choose Technogeeks?
If you are exploring data science with an Artificial Intelligence Course in Mumbai, AI Courses in Mumbai, or an advanced AI Course in Mumbai, choose a program that combines practical learning with industry-focused training.
Technogeeks provides live instructor-led classes, real-world projects, case studies, and expert guidance to help learners build practical skills in data science, machine learning, and artificial intelligence.
Highlights of the Course
- 100% Placement Assistance
- Live Instructor-Led Training
- Industry-Experienced Trainers
- Real-Time Projects & Case Studies
- Practical Training with Modern AI Tools
- Resume Building & Mock Interview Preparation
- One-Year Access to Learning Resources
- Industry-Oriented Curriculum
- Hands-On Assignments and Practical Exercises
Data Science Course Duration and Learning Format
The data science course duration depends on the training format, course curriculum, and learning schedule. A well-structured program typically combines classroom learning with practical exercises, assignments, hands-on projects, and revision sessions.
Technogeeks provides a learning approach that includes:
- Live training with instructors
- Hands-on coding practice
- Topic-based assignments
- Real-world examples and case studies
- Practical project work
- Doubt-clearing sessions
- Interview preparation
- Resume support
- Placement support
Online Data Science Course with Placement Support
For learners who cannot attend classroom sessions on a daily basis, we have an online data science course with placement support that can provide a flexible way to learn from home or even if you are working.
Online training including live instructor sessions, practical demonstrations, assignments, project work, doubt-solving, and access to learning resources. Learners can work on projects while receiving guidance from trainers.
Data Science Course Fees and Career Opportunities
Before enrolling in any course, students should compare the Data Science Course Fees, duration, training format, practical projects, and placement support. Fees depend on the course structure that they are offering, just like learning mode, practical training, and support provided by the institute.
When we are comparing the data scientist course fee and data analytics course fee, consider the overall value of what they are including projects, trainer support, interview preparation, and placement assistance.
Those students who are interested in analytics can start with a Data Analyst Course in Mumbai to learn about Excel, SQL, Python, Power BI, Tableau, and data visualization. After creating a strong foundation, they can easily move into data science to develop advanced technical and machine learning skills.
The data science course fees and duration can be different from other institutes, so learners should compare the curriculum, practical training, and career support before choosing a course.
Why Learn Data Science with Artificial Intelligence?
Today, many data-related jobs use automation, smart systems, predictive models, and large amounts of data. Learning Data Science with Artificial Intelligence can help students to understand these technologies and use them in real-world projects to get better results.
An artificial intelligence and data science course can help learners to understand these:
- Machine Learning and model building
- Deep Learning techniques
- Natural Language Processing (NLP)
- Computer Vision applications
- Generative AI concepts
- Large Language Models (LLMs)
- Predictive Data Analysis
- Intelligent Automation
- AI-powered Data Analysis
Who Can Join This Course?
Our data science course is basically designed for learners, IT background, non-it background and working prefessionals. You can consider joining if you are:
- Graduates looking to begin a career in Data Science
- Engineering and Computer Science students
- Graduates from B.Sc., BCA, B.Com., BBA, MCA, or M.Sc. programs
- Working professionals planning to switch careers
- Software developers and test engineers
- Business analysts and data analysts
- Professionals who want to improve their data and analytical skills
- Learners interested in Machine Learning and Artificial Intelligence
Those students who are searching for a Data Science Course After 12th can also start with foundational programming, mathematics, statistics, and data concepts before moving to advanced topics.
The data science course eligibility generally depends on the institute and program structure. A basic understanding of mathematics, logical reasoning, and computers can be helpful, while programming knowledge can be developed during the course.
Career Opportunities After Data Science Training
Data science training can help you to explore different career options in technology and analytics. During the course, you can develop technical and practical skills that can prepare you for various roles. Depending on your skills, education, and experience, you can apply for positions such as:
- Data Scientist
- Data Analyst
- Machine Learning Engineer
- Python Developer
- Machine Learning Analyst
- AI/ML Professional
A good Data Scientist Training Institute in India will provide you technical training, practical projects, real-world assignments, and career support to help students for job opportunities.
At Technogeeks, learners gain practical experience through live classes, hands-on projects, real-world case studies, resume support, mock interviews, and placement assistance.
Course Curriculum
- What is Python and brief history
- Why Python and who use Python
- Discussion on Python 2 and 3 Unique features of Python
- Discussion on various IDE's
- Demonstration of practical use cases
- Python use cases using data analysis
- Installing python Setting up Python environment for development
- Installation of Jupyter Notebook
- Setting up Python environment for development
- How to access python course material using Jupyter
- Write your first program in python
- Python built-in functions
- Number objects and operations Variable assignment and keywords String objects and operations Print formatting with strings
- List objects and operations
- Tuple objects and operations
- Dictionary objects and operations
- Sets and Boolean
- Object and data structures assessment test
- Introduction to Python statements
- If, elif and else statements
- Comparison operators
- Chained comparison operators
- What are loops
- While loops
- Useful operators
- List comprehensions
- Statement assessment test
- Game challenge
- Methods What are various types of functions
- Creating and calling user defined functions
- Function practice exercises
- Lambda Expressions
- Map and filter
- Nested statements and scope
- Args and kwargs
- Functions and methods assignment
- Milestone Project (Making tic-tac-toe in python)
- Process files using python
- Read/write and append file object
- File functions
- File pointer and operations
- Introduction to error handling
- Try, except and finally
- Python standard exceptions
- User defined exceptions
- Unit testing
- File and exceptions assignment
- Python inbuilt modules
- Creating UDM-User defined modules
- Passing command line arguments
- Writing packages
- Define PYTHONPATH
- Name and Main
- Object oriented features Implement
- Object oriented with Python
- Creating classes and objects
- Creating class attributes
- Creating methods in a class
- Inheritance
- Polymorphism
- Special methods for class
- Assignment - Creating a python script to replicate deposits and withdrawals in a bank with appropriate classes and UDFs.
- Collections module
- Datetime module
- Python debugger
- Timing your code
- Regular Expressions
- StringIO
- Python decorators
- Python generators
- Python inbuilt modules
- Install packages on python
- Introduction to pip, easy install
- Multithreading
- Multiprocessing
- SQL integration with Python
- Table operations in SQL using Python
- CRUD operations in SQL
- Working on multiple tables using Python and SQL
- What is SQL?
- Why we need SQL Integration with Python
- Data types in SQL
- DDL, DML, TCL sub languages in SQL
- Significance and type of Joins in SQL
- Where clause in SQL
- Group by clause in SQL
- Create command in SQL
- Insert command in SQL
- Select command in SQL
- Select command variants in SQL
- Update command in SQL
- Delete command in SQL
- Drop command in SQL
- Truncate command in SQL
- REST principles
- Creating application endpoints
- Implementing endpoints
- Using Postman for API testing
- Python , Database and Front end integration concept, implementation
- Commit and rollback concept in SQL
- Introduction in Excel
- Data Cleaning & Preparation
- Formatting & Conditional Formatting
- Lookup Function
- Analyzing data with Pivot Tables
- Charts
- Data Visualization/Dashboarding using excel
- Data Analysis using statistics
- Lookup Function
- Introduction to data analysis
- Data analysis and Artificial Intelligence Bridge and connecting it to database.
- Introduction to Data Analysis libraries
- Data analysis introduction assignment challenge
- Why Data analysis?
- Introduction to Numpy arrays
- Creating and applying functions
- Numpy Indexing and selection
- Numpy Operations
- Exercise and assignment challenge
- Introduction to Series
- Introduction to DataFrames
- Data manipulation with pandas
- Missing data
- Groupby
- Operations
- Data Input and Output
- Pandas in depth coding exercises
- Text data mining and processing Data mining applications in Data engineering
- File system integration with Pandas
- Excel integration with Pandas
- Operations on Excel using dataframe
- Data aggregation on Excel Data
- Data visualization using Excel data
- Milestone Project – 2
- Plotting using Matplotlib Plotting
- Numpy arrays
- Plotting using object-oriented approach
- Subplots using Matplotlib
- Exercise and assignment challenge
- Matplotlib attributes and functions
- Matplotlib exercises
- Comparison Between Power BI & Programming Based Data Visualization
- Need of Power BI
- Types of Data Sources Supported by Power BI for Report Development
- How to Build Report & Dashboard in Power BI
- How to Build Charts in Power BI
- Data Visualization Using Power BI Features
- Types of Graphs
- Multiple Graphs Combinations
- Multiple File Formats Supported in Power BI
- Data Analysis Without Visualization
- Data Analysis With Visualization
- Need of Mathematics for Data Science
- Exploratory Data Analysis (EDA)
- Numeric Variables
- Qualitative and Quantitative Analysis
- Types of Data Formats
- Measuring the Central Tendency – The Model
- Measuring Spread – Variance and Standard Deviation
- Euclidean Distance
- Understanding Parametric Tests
- Confidence Coefficient
- Understanding Machine Learning
- Scope of ML
- Supervised and Unsupervised learning
- Introduction to Artificial Intelligence
- Introduction to Machine Learning
- Need of Machine learning in forecasting
- Demand of forecasting analytics in current industrial trends
- Introduction to Machine Learning Algorithms Categories
- Introduction to Regression
- Exercise on Linear Regression using sci-kit learn Library
- Project on Linear regression using USA_HOUSING data
- Evaluation of Linear regression using python visualizations
- Practice project for Linear regression using advertisement data set to predict appropriate advertisements for users.
- Introduction to Regression
- Project on Logistic regression using Dogs and horses' dataset
- Getting the correct number of clusters
- Standard scaling problem
- Practice project on KNN algorithm
- Intuition behind Decision trees
- Implementation of decision tree using a real time dataset
- Ensemble learning
- Decision tree and random forest for regression
- Decision tree and random forest for classification
- Evaluation of the decision tree and random forest using different methods
- Practice project on decision tree and random forest using social network
- Data to predict if someone will purchase an item or not
- Linearly separable data Non-linearly separable data
- SVM project with telecom dataset to predict the users portability
- Introduction to PCA Need for PCA
- Implementation to select a model on breast-cancer dataset
- Model evaluation
- Bias variance trade-off
- Accuracy paradox
- CAP curve analysis
- K-means Clustering Intuition
- Implementation of K-means with Python Using Mall Customers Data to Implement Clusters on the Basis of Spending and Income
- Hierarchical Clustering Intuition
- Implementation of Hierarchical Clustering with Python
- A priori theory and explanation
- Market basket analysis
- Implementation of Apriori
- Evaluation of association learning
- POC - To make a model to predict the relationship between frequently bought products together on the given dataset from a supermarket.
- Introduction to Natural Language processing
- NLTK Python library
- Data stemming technique
- Data Vectorization
- Exercise on NLTK
- POC - Apply NLP techniques to understand reviews given by customers in a dataset and predict if a review is good/bad without human intervention
- Neural Network and Deep Learning
- What is TensorFlow?
- TensorFlow Installation
- TensorFlow basics
- TensorFlow with Contrib Learn
- TensorFlow Exercise
- Keras Basics
- Pipeline implementation using Keras
- MNIST implementation with Keras
- Cloud integration with AWS cloud computing
- Hadoop
- HDFS
- Hive
- ETL Development with Python Scripting in Pandas
- Introduction to Generative AI
- Evolution of Generative AI in Industry
- Discriminative Models
- Generative Models
- Difference between Discriminative and Generative Models
- Overview of Foundation Models
- Overview of Large Language Models (LLMs)
- How Foundation Models and LLMs Power Today's AI Assistants and Tools
- Popular Generative AI Tools
- ChatGPT
- Gemini
- Copilot
- Neural networks foundations
- Understanding the Transformer architecture and attention
- Tokenization, embeddings and vector representations
- Calling LLM APIs with Python
- Retrieval-Augmented Generation (RAG) with custom data
- Vector databases and semantic search
- Building apps with LangChain
- Mini project - a document Q&A bot
- Zero-shot and few-shot prompting
- Chain-of-thought prompting, prompt patterns and
- Responsible AI use
- Project use cases Introduction
- Project Scenarios
- Project life cycle
- What is version controlling in project management
- What is GitHub
- Significance of GitHub in project management
- Code submission for testing and deployment
- Predictive analytics tools and techniques
- Project best practices
Our trainers are experts in their fields. They simplify complex concepts for the students and make them easy to understand. They solve each and every type of student's query. Their teaching method is more focused on real-time examples, preparing the students for industry interviews. Students will have one-on-one coaching sessions with them so that they will be able to ask questions at any time.
Key Highlights of Our Trainers:
- Certified Professionals with Over 8 Years of In-Depth Experience
- Imparted Knowledge to Over 2,000 Students Annually
- Demonstrated Strong Theoretical and Practical Expertise in Their Respective Domains
- Possess Expert-Level Subject Knowledge and Stay Current with Real-World Industry Applications
Why Choose Technogeeks?
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Frequently Asked Questions
Yes. Data Science is an in-demand, future-ready career with opportunities in the field of AI, Machine Learning, Business Intelligence, FinTech, Healthcare, E-commerce, and IT. Students can pursue a Data Science Course After 12th and build Python, SQL, Statistics, Machine Learning, and Data Visualization skills. You can build a rewarding career.
If you are planning to become a data scientist then first you have to learn all the things required to become a data scientist. You can follow below data science roadmap :
Python + SQL → Statistics → Data Cleaning → EDA → AI and Machine Learning → Deep Learning → NLP → Projects → Portfolio → data science Job/data science Internship.
Practical data science projects with AI automation and industry-relevant tools are essential.
A job ready Data Science training in Mumbai can cover:
Python | SQL | Excel | Pandas | NumPy | Matplotlib | Seaborn | Statistics | Power BI | Tableau | Machine Learning | Deep Learning | NLP | AI | Jupyter Notebook | Git/GitHub | Real-world Data Science Projects
If you're looking for AI Driven Data Science & Data Analytics training in Mumbai with placement, TechnoGeeks can help you build job-ready skills through hands-on learning, projects, internship letter and industry-oriented training.
No genuine data science institute can guarantee a job. Because candidates must have skills which companies want.Instead, look for placement assistance, live projects, mock interviews, and resume preparation. Strong Data Science and AI skills have high industry demand.
Technogeeks Data science Training in Mumbai in which we provides placement support, interview preparation, and career guidance to help students become job-ready
AI helps Data Scientists:
- Automate data analysis
- Build predictive models
- Improve forecasting accuracy
- Detect fraud and anomalies
- Create recommendation systems
- Develop intelligent business solutions
Today, AI is changing how businesses use data, making AI-powered Data Science one of the most valuable and secure career paths.
Yes, Data Science can be a good career option in India. Many companies want professionals who can analyze data, find useful insights, and help to make business decisions. A Data Science Course in India can help learners develop skills in Python, SQL, statistics, data analysis, and machine learning.
Data Science can be difficult when you take a first step because it includes programming, mathematics, statistics, and analytical thinking but if you take proper training and do regular practices, beginners can learn these skills step by step. A well-structured Data Science Course can make the learning process easier through practical exercises and projects.
In Data Science with Statistics you can understand data, identify patterns, and make better decisions. It has concepts like probability, averages, distributions, correlation, and regression. Learning statistics is an important part of Data Science Training .
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Data Science course Certification Training locations in Mumbai:
Andheri East [400069], Andheri West [400058], Bandra East [400051], Bandra West [400050], Borivali East [400066], Borivali West [400092], Kandivali East [400101], Kandivali West [400067], Malad East [400097], Malad West [400064], Goregaon East [400063], Goregaon West [400062], Santacruz East [400055], Santacruz West [400054], Dadar East [400014], Dadar West [400028], Kurla East [400024], Kurla West [400070], Ghatkopar East [400077], Ghatkopar West [400086], Mulund East [400081], Mulund West [400080], Bhandup East [400042], Bhandup West [400078], Vikhroli East [400083], Vikhroli West [400079], Chembur East [400071], Chembur West [400089], Wadala East [400037], Wadala West [400031]
Locations Offered:
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