Data Science, Artificial Intelligence and Machine Learning Course in Ahmedabad

Master AI, Machine Learning, and Data Science with real-world projects.
  • Comprehensive AI & ML Curriculum
  • Hands-on Learning with Real-World Datasets
  • Career Guidance & Freelance Support
  • Industry-Ready Certification
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About AI/ML Course

Data science is a broad field which uses computers math, statistics and artificial intelligence analyse huge amounts of data and provide business insights that are actionable. Data scientists can provide valuable insights into past events and their causes future projections, as well as possible actions to take by identifying trends and patterns. Businesses could gain a competitive edge, improve their the efficiency of their operations and make better informed decisions based on these insights. Our other basic but advanced course in DTP Course in Ahmedabad available at Rednwhite Institute.

Giving students a strong foundation in Python programming and its applications in AI and ML is the goal of the Artificial Intelligence and Machine Learning course. Rednwhite offers Artificial Intelligence and Machine Learning Course in Surat. So Students will learn how to build AI/ML algorithms, work with well-known libraries and frameworks, and develop real AI/ML solutions in Python in this course.

duration
Duration

18 Months

schedule
Schedule

4+2 Hours Daily

Eligibility
Eligibility

BCA, MCA, CE, IT, 12th Pass (Science)

Prerequisites

  • BCA, MCA, CE, IT, 12th Pass (Science), Statistics Background
  • Basic Programming Knowledge Recommended
  • Passion for AI & Machine Learning

Technologie & Tools You'll Master

Python

Python

SQL

SQL

TensorFlow

TensorFlow

Power BI

Power BI

NLP

NLP

Course Curriculum

Our comprehensive curriculum is designed with industry needs in mind, ensuring you're job-ready upon graduation.

Python for Data Science
  • Python and Jupyter Notebook Basic Introduction
  • Data Types, Variables & Operators
  • Control Structures & Looping
  • Functions & Modules
  • NumPy for Numerical Data Handling
  • Pandas for Data Manipulation
  • Matplotlib & Seaborn for Data Visualization
  • Exploratory Data Analysis (EDA)
  • Data Cleaning & Preprocessing
  • Introduction to Databases & SQL
  • Data Retrieval (SELECT, WHERE, ORDER BY)
  • Filtering & Aggregation (GROUP BY, HAVING)
  • Joins (INNER, LEFT, RIGHT, FULL)
  • Subqueries
  • Data Manipulation (INSERT, UPDATE, DELETE)
  • Window functions
  • Case expressions
  • Basic & Advanced Formulas
  • Conditional Formatting & Data Validation
  • Pivot Tables & Charts
  • Lookup Functions (VLOOKUP, HLOOKUP, XLOOKUP)
  • Data Cleaning & Transformation
  • Introduction to BI & Data Visualization
  • Connecting & Importing Data
  • Data Modeling & DAX Functions
  • Creating Interactive Dashboards
  • Advanced Charts & Visuals
  • Power Query for Data Transformation
  • Understanding Real-World Business Problems
  • Defining Key Performance Indicators (KPIs)
  • Data-Driven Decision Making
  • Hands-on Business Case Analysis
  • Applying Python, SQL, Excel & Power BI in Business Scenarios
  • Presentation & Report Writing
  • Introduction to Machine Learning and Types of Learning
  • Supervised Learning: Linear/Logistic Regression, Decision Trees
  • Unsupervised Learning: Clustering, K-Means, PCA
  • Model Evaluation and Metrics
  • Feature Engineering & Model Selection
  • Hands-on with Scikit-learn
  • Fundamentals of Neural Networks
  • Activation Functions and Backpropagation
  • Deep Learning Architectures: CNNs, RNNs, LSTMs
  • ntroduction to TensorFlow and Keras
  • Model Optimization and Regularization
  • Building Deep Learning Models for Real-World Applications
  • AI Fundamentals and its Role in Automation
  • Reinforcement Learning
  • Natural Language Processing (NLP): Text Processing and Tokenization
  • Computer Vision with OpenCV and CNN
  • Implementing AI in Real-World Applications
  • Data Visualization Techniques
  • Visualizing Data with Excel and Power BI
  • Building Interactive Dashboards
  • Data Storytelling and Communicating Insights
  • Advanced Visualization Techniques with Python (Matplotlib, Seaborn)
  • Working on an Industry-Oriented AI/ML Project
  • End-to-End Data Science Pipeline Implementation
  • Model Deployment and Evaluation
  • Presenting Insights and Solutions to Real-World Problems

What You Will Learn

This course will help you understand data, analyze it, and prepare you for a professional career as a Data Analyst!

Excel
Microsoft Excel

Data handling, formulas, pivot tables & data visualization.

Formulas Pivot Tables Data Charts
SQL
SQL (Structured Query Language)

Database management and query writing skills.

Database Queries MySQL
Python
Python for Data Analysis

Data processing using pandas, numpy, and matplotlib.

Pandas NumPy Matplotlib
Power BI
Data Visualization

Present data using graphs and charts in Power BI.

Power BI Data Charts Visualization
Projects
Real-world Projects

Hands-on projects for real-world industry applications.

Hands-on Learning Industry Projects