Data Science Course in Mumbai – Master AI, Machine Learning & Analytics
Job-oriented, AI Driven hands-on interactive Data Science training with real-time 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
Nowadays the demand for data professionals increases rapidly across banking, healthcare, retail, e-commerce, manufacturing, and IT are dependent on data to 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 training program that is designed for students, graduates and working professionals. Whether your goal is to pursue a Masters in Data Science or secure a high paying job in the data science field, then Technogeeks AI driven data science course is basically designed to strengthen your technical skills to build a successful career in data science and artificial intelligence.
Why Choose Technogeeks?
If you are looking for a Data Science Course in Mumbai, an Artificial Intelligence Course in Mumbai, AI Courses in Mumbai, or an advanced AI Course in Mumbai, Technogeeks offers a complete Data Science and AI program in Mumbai that designed to make you industry ready with hands on training, real world projects, and expert mentorship. Our course includes Data Science, Machine Learning, and Artificial Intelligence to prepare you for high demand careers. Ideal for learners our aim is to upgrade your skill or advance in AI and data science roles.
Highlights of the Course
- 100% Placement Assistance
- Live Instructor-Led Training
- Industry-Experienced Trainers
- Real-Time Projects & Case Studies
- Free AI Tools Training (ChatGPT, Gemini and More)
- Resume Building & Mock Interview Preparation
- One-Year Access to Learning Resources
Data Science Course Fees and Career Opportunities
Many students compare Data Science Course Fees before enrolling in any institute. While Data Science Course Fees will be different from other institutes, it is important to choose a course that provides hands-on projects, placement assistance, and an industry relevant AI curriculum to increase your long term career growth.
Those students who are interested in analytics can also benefit from the Data Analyst Course in Mumbai, where they will learn about Excel, SQL, Python, Tableau, and Power BI before progressing to machine learning and Artificial Intelligence.
Who Can Join This Course?
If you are planning a Data Science Master skills, pursuing Masters in Data Science, or looking for a professional certification, this course is beneficial for you:
- Students after graduation
- Students looking for a Data Science Course After 12th (through foundation learning)
- Engineering and Computer Science students
- B.Sc., BCA, B.Com., BBA, MCA, and M.Sc. graduates
- Working professionals looking to switch careers
- Software Developers and Test Engineers
- Business Analysts and Data Analysts
- Anyone interested in AI and Data Science
Those students who are searching for a Data Scientist Training Institute in India should focus on gaining practical skills along with their education. At Technogeeks, you learn through live training, hands-on projects, and real world case studies, helping you build the skills needed for a successful career in Data Science and Artificial Intelligence.
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?
Everything you need to launch your career in tech
Tools & Technologies You'll Master
23+ industry-standard tools covered in this program
Book Your Seat Today!
Start your journey with just ₹5,000. Watch a free demo first — pay the rest only after you're confident. No-cost installments available.
Training to Placement Journey
From your first session to landing your dream job — every step mapped out.
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. With strong 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 roadmap :
Python + SQL → Statistics → Data Cleaning → EDA → AI and Machine Learning → Deep Learning → NLP → Projects → Portfolio → Job/Internship.
Practical data science projects with AI automation and industry-relevant tools are essential.
A job ready Data Science course 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 Projects
If you're looking for AI Driven Data Science & Data Analytics training in Mumbai, TechnoGeeks can help you build job-ready skills through hands-on learning, projects, internship letter and industry-oriented training.
No genuine 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 IT Training institute 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.
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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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