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AI-Driven Data Science Course

No prior experience needed! In just 12 months, master AI-powered Data Science skills with 100% practical training, real-world projects, and career support. Become industry-ready and unlock high-paying job opportunities.

Data analytics with BI

5 months Accelerator
Package: 4-5.5 LACS
Job Role: Data Analyst

Data science and ML

8 months bootcamp
Package: 5-7 LACS
Job Role: ML Engineer

AI driven data science

12 months mastery program
Package: 8-10 LACS
Job Role: Data Scientist

About Course

Today’s data landscape demands more than just technical skills; it requires practical application, critical thinking, and constant adaptation. NDMIT directly addresses this industry skill gap by preparing you for the real data science world.

We offer job-ready expertise through hands-on projects, simulations, and training with next-generation technologies like generative AI, PySpark, Databricks, and Power BI. Learn from expert faculty in a comprehensive curriculum that builds both technical and essential professional skills, ensuring you’re equipped for immediate impact.

Key Learning Outcomes

✅ Master essential data science concepts and tools in a data-driven world.

✅ Gain hands-on experience through real-world projects and simulations.

✅ Develop critical thinking and problem-solving skills for data challenges.

✅ Learn to deploy and monetize data models effectively.

✅ Become proficient in next-generation technologies like Generative AI.

✅ Cultivate professional and communication skills vital for data roles.

Course Module

  • Data Storytelling and Visualization
  • Business Acumen and Problem Solving
  • Communication and Interpersonal Skills
  • Career Preparation
  • Introduction to Power BI
  • Data Connectivity & Transformation
  • Data Modeling & Relationships
  • DAX (Data Analysis Expressions)
  • Building Interactive Dashboards
  • Power BI Deployment & Security
  • Excel Fundamentals
  • Excel Functions
  • Data Cleaning & Transformation
  • Data Analysis with Excel
  • Project Templates
  • Introduction to RDBMS
  • Entity Relationship (ER) Diagram
  • Normalization
  • OLTP and OLAP
  • Performance Optimization
  • Introduction to SQL
  • SQL Basics
  • Data Aggregation and Grouping
  • Joins and Relationships
  • Window Functions
  • Indexes and Materialized Views
  • Project
  • Python Fundamentals
  • Python Flow Control
  • Python Data Types
  • Python Functions
  • Python Files
  • Python Exception Handling
  • Python Object and Class
  • Python Advanced Topics
  • Python Date and Time
  • Numpy
  • Introduction to Pandas
  • Data Handling with Pandas
  • Data Transformation with Pandas
  • Exploratory data analysis with Pandas
  • Matplotlib
  • Seaborn
  • Project
  • Descriptive statistics
  • Measures of Central Tendency
  • Inferential statistics
  • Hypothesis testing
  • Probability distributions
  • Parametric and Non-parametric Algorithms
  • Feature Selection
  • Data Imputation
  • Linear Regression
  • Logistic Regression
  • Decision Trees
  • Random Forest
  • K nearest neighbour (KNN)
  • K-means Clustering (Kmeans)
  • Model Evaluation Techniques
  • Exponential Smoothing
  • Holt Winter
  • ARIMA and SARIMA
  • Prophet
  • Concept
  • Bagging
  • Boosting
  • XGBoost
  • AdaBoost
  • Model Tuning
  • GridSearch
  • Cross Validation
  • AUC ROC Curve
  • Customer Segmentation
  • Market Basket Analysis
  • Demand Forecasting
  • Recommendation Models
  • Monetizing ML models
  • MLOps
  • Natural Language Processing (NLP)
  • Sentiment Analysis
  • RAG Applications
  • AI AGents
  • Project
  • Clusters, Notebooks, Workflows
  • Databricks SQL
  • Lakehouse Architecture
  • Data Governance
  • MLflow
  • Introduction to PySpark and Big Data
  • Working with PySpark dataframes
  • Data Processing and Transformation
  • PySpark SQL and Query Optimization
  • Project
  • Need for cloud
  • Cloud computing
  • Major players

What you will achieve

Certification/ Accreditation

Reach Out

      1-on-1 Career Counseling.
      Live Doubt-Clearing Session.
      ₹499 Fully Adjustable in Fees”.
      Personalized Roadmap Provided.

    ₹999.00 ₹499

    What Does This Course Have to Offer

    Need to know more

    Ready to dive deeper into the world of Data Science? Our program is meticulously designed to equip you with the practical skills and industry knowledge needed to excel. Discover how our expert-led training, hands-on projects, and cutting-edge curriculum will transform you into a job-ready professional.

    Download our brochure to get a comprehensive overview of modules, career opportunities, and how NDMIT prepares you for success in this high-demand field.

    Which Program is Best in The Market

    At NDMIT, we offer specialized Data Science programs tailored to various career aspirations. Our Data Science with Power BI course is ideal for aspiring Data Analysts and Business Intelligence professionals, focusing on powerful data visualization and reporting. For those aiming to be Machine Learning Engineers or Data Scientists, our Data Science with Machine Learning (ML) program delves into building robust predictive models. Lastly, our AI-Driven Data Science Course is perfect for future-focused professionals eager to specialize in cutting-edge AI applications, including Generative AI.

    Certified Data Analyst
    (CDA)

    • Fundamentals of Power BI and Business Intelligence.

    • Data connectivity, transformation, and cleansing workflows.

    • DAX (Data Analysis Expressions) for advanced calculations.

    • Creating dynamic and interactive Power BI dashboards.

    • Deployment, sharing, and security in Power BI.

    • SQL essentials for data retrieval and management.

    • Python basics for data handling and exploratory analysis.

    Certified Data Scientist - ML Track (CDS-ML)

    • Professional skills development and SQL foundations.

    • Python programming with NumPy, Pandas, Matplotlib, and Seaborn.

    • Statistics for Data Science: descriptive, inferential, and probability.

    • Core machine learning algorithms: regression, trees, KNN, and clustering.

    • Time series forecasting and predictive modeling.

    • Ensemble methods and hyperparameter tuning.

    • Business Intelligence with Power BI dashboards and DAX.

    Certified Data Scientist - AI Track (CDS-AI)

    • Professional skills, Excel, and database fundamentals.

    • Python programming with data analysis libraries (NumPy, Pandas, Seaborn).

    • Statistics for Data Science: descriptive, inferential, and hypothesis testing.

    • Core ML, ensemble methods, and time series forecasting techniques.

    • Advanced hyperparameter tuning and model optimization.

    • Generative AI, NLP techniques, and AI-powered agents.

    • Big Data processing, cloud integration, and model deployment.

    Learn With a World-Class Curriculum

    Duration

    5 Months

    Description

    Learn to analyze data using foundational tools. This program covers Excel, SQL, and Python to clean and transform data, build interactive dashboards with Power BI, and develop key professional skills for a successful career in data analysis.

    Topics Covered

    • Excel & Database Fundamentals

    • Python & SQL for Data Analysis

    • Business Intelligence with Power BI

    Duration

    8 Months

    Description

    Master the core of machine learning with a focus on practical applications. This course covers everything from Python and SQL fundamentals to machine learning algorithms, time series forecasting, and model tuning for real-world projects.

    Topics Covered

    • Python, Libraries, & SQL

    • Machine Learning Algorithms

    • Ensemble & Time Series Techniques

    Duration

    12 Months

    Description

    Become an AI expert by mastering Python, machine learning, and advanced generative AI concepts. Learn to deploy models using MLOps, work with big data in PySpark, and utilize Databricks for a comprehensive skill set.

    Topics Covered

    • Python, Libraries, & SQL

    • Machine Learning & Generative AI

    • Big Data & Cloud Concepts

    Student Testimonials

    Career Opportunities

    Data Analyst:

    Data insights specialist, Business Intelligence (BI) Analyst

     

    Machine Learning (ML):

    ML Engineer, AI Researcher, Deep Learning Scientist

     

    Scientist:

    Predictive Modeler, Statistical Analyst, Big Data Expert

     

    Consulting:

    Data Strategy Consultant, Analytics Advisor, AI Solutions

    Frequently Asked Question

    • A Data Analyst focuses on understanding past data. An ML Engineer builds and deploys AI models. A Data Scientist uses stats and coding to find insights and make predictions.

    Almost every industry! Tech, finance, healthcare, retail, marketing, and even government agencies are all looking for data and AI talent.

    A foundational understanding of math and statistics is helpful, especially for Data Science and ML. However, many programs teach you the practical math you’ll need.

    1. It varies, but with dedicated learning and practical projects, many individuals find entry-level positions within 6-12 months after completing a specialized program.

    Still Have Questions? We’re Just a Click Away.

    Don’t hesitate to reach out! We’re here to help clarify any doubts you have. Whether you need more details about our courses, career paths, or anything else, our team is ready to provide the answers you need.

    Take Demo Online

    Ready to explore your future? Take our free online demo, it’s just like a personalized career counseling session, designed to guide your path.

     
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