Data Science, Artificial Intelligence and Machine Learning Course in Ahmedabad
Master AI, Machine Learning, and Data Science with real-world projects.
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Comprehensive AI & ML Curriculum
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Hands-on Learning with Real-World Datasets
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Career Guidance & Freelance Support
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Industry-Ready Certification
Elite Training Program
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
18 Months
Schedule
4+2 Hours Daily
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
SQL
TensorFlow
Power BI
NLP
Course Curriculum
Our comprehensive curriculum is designed with industry needs in mind, ensuring you're job-ready upon graduation.
- 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!
Microsoft Excel
Data handling, formulas, pivot tables & data visualization.
SQL (Structured Query Language)
Database management and query writing skills.
Python for Data Analysis
Data processing using pandas, numpy, and matplotlib.
Data Visualization
Present data using graphs and charts in Power BI.
Real-world Projects
Hands-on projects for real-world industry applications.
