Data Science, Artificial Intelligence and Machine Learning Course in Surat
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 field of study that uses computers math, statistics and artificial intelligence study massive amounts of data to gain actionable business insights. Data scientists can provide important insights into past events as well as their causes future projections, as well as possible actions to take by finding patterns and trends. Businesses can gain an competitive edge, enhance their processes, and take informed decisions based on these insights. Desktop Publishing or DTP Course in Surat is also offered at our institute.
A solid basis in Python programming and its applications in the fields of artificial intelligence and machine learning are what the Python for Artificial Intelligence and Machine Learning course aims to give students. The objective of this course is to provide students with the knowledge they need to apply AI/ML algorithms, interact with popular libraries and frameworks, and create useful AI/ML applications using Python. We also offer AI ML Courses in Ahmedabad for Python.
Duration
16 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.
