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The Best Data Science Course With AI
Coderzon Technologies offers an exceptional Data Science with AI course designed to equip you with the skills needed for success in the data-driven world. Our training includes expert instruction in data science methodologies, machine learning algorithms, and artificial intelligence techniques. With a focus on both foundational data science principles and advanced AI applications, our course ensures you gain a comprehensive understanding of data analysis, predictive modeling, and AI integration. Benefit from our 100% job placement assistance and receive training from industry experts to launch your data science career with confidence.
Admission Process
There are 3 simple steps in the Admission Process which is detailed below
01
Fill the Application Form
Apply to our Data Science Course With AI by filling a simple online application form to kick-start the admission process.
02
Interview Process & Demo Session
Go through a screening call with Admissions office and Book your demo.
03
Join the Program
Block your seat for Data Science Course With AI with a payment of ₹ 1000 to begin learning with prep course.
What You Will Learn In Our Data Science Course With AI
Introduction to Data Science and AI
Overview of Data Science and AI
- Understanding the field of data science and AI
- History and evolution of AI
- Real-world applications of data science and AI
Tools and Technologies
- Introduction to Python and its libraries
- Setting up the development environment
Data Manipulation and Cleaning
Data Structures and Manipulation with Pandas
- Series and DataFrames
- Data selection, filtering, and transformation
Data Cleaning Techniques
- Handling missing data
- Removing duplicates
- Data normalization and scaling
Exploratory Data Analysis (EDA)
Statistical Analysis
- Descriptive statistics
- Probability distributions
Data Visualization
- Basics of Matplotlib and Seaborn
- Creating histograms, bar plots, box plots, and scatter plots
Machine Learning Basics
Supervised Learning
- Linear Regression
- Logistic Regression
- Decision Trees and Random Forests
Unsupervised Learning
- Clustering (K-means, Hierarchical)
- Principal Component Analysis (PCA)
Advanced Machine Learning
Model Evaluation and Optimization
- Train-test split, cross-validation
- Performance metrics (accuracy, precision, recall, F1-score)
- Hyperparameter tuning (GridSearchCV, RandomSearchCV)
Ensemble Methods
- Boosting (AdaBoost, Gradient Boosting)
- Bagging and stacking
Deep Learning Fundamentals
Introduction to Neural Networks
- Perceptron and multilayer perceptron
- Backpropagation and gradient descent
Convolutional Neural Networks (CNNs)
- Architecture of CNNs
- Implementing CNNs with TensorFlow/Keras
Recurrent Neural Networks (RNNs)
- Understanding RNNs and LSTMs
- Applications in time-series data and text analysis
AI Techniques and Applications
Natural Language Processing (NLP)
- Text preprocessing and tokenization
- Sentiment analysis and text classification
- Word embeddings (Word2Vec, GloVe)
Computer Vision
- Image processing and augmentation
- Object detection and recognition
AI Use Cases and Ethical Considerations
- AI applications across various industries
- Ethical considerations in AI
Capstone Project
Project Planning and Execution
- Choosing a real-world data science problem
- Data collection, cleaning, and preprocessing
- Model building, evaluation, and optimization
Final Project Presentation and Review
- Presenting the capstone project
- Review and feedback
Career Preparation
Crafting a Data Science Resume
- Highlighting relevant projects and skills
Personal Branding
- Enhancing profiles on LinkedIn and GitHub
Technical Interview Preparation
- Mock interviews and practice
Why Choose Our Data Science Course With AI?
- Expert Instructors: Learn from experienced professionals who bring real-world knowledge and practical insights.
- Hands-On Projects: Work on real-time projects to apply what you’ve learned and build a robust portfolio.
- Comprehensive Curriculum: Cover all aspects of the Data Science With AI , ensuring a complete understanding of the technology.
- Career Support: Receive 100% placement assistance to help you transition smoothly into the tech industry.
New Batch Opening For Data Science Course(AI)
Next Batch
Cochin: Aug 12th 2024 (Offline & Online)Duration: 6 Months, 5 Days a Week, 2 Hours/day
Course Fees:
Fees (One time Payment mode) 62,000
Fees (EMI Mode) 70,000
Registration Fee: 1000
Certification: Course completion certificate from coderzon.
For New Admissions Click Enroll Button
Course Overview
Data Science has emerged as a pivotal field in technology, with Artificial Intelligence (AI) driving groundbreaking advancements across various industries. Its ability to analyze vast amounts of data and generate actionable insights makes it an indispensable tool for modern decision-making. This Data Science with AI course is designed to equip you with the knowledge and skills necessary to harness the power of AI in data analysis and machine learning.
Our Data Science Course with AI offers an in-depth exploration of advanced data science methodologies and cutting-edge AI technologies. You will develop proficiency in essential tools and libraries for data manipulation and analysis, including Python, Pandas, and NumPy. The course covers key AI concepts and algorithms, such as machine learning models, neural networks, and natural language processing. You’ll also gain hands-on experience with practical AI applications, including predictive analytics and automation, to address real-world challenges. By emphasizing modern data science techniques and AI practices, this course equips you with the skills needed for a successful career in the rapidly evolving field of data science.
Technologies Covered in the Data Science Course With AI
- Python: Core language for data analysis.
- R: Additional language for statistical analysis.
- SQL: Query language for database management.
- Pandas: Data manipulation and analysis.
- NumPy: Numerical computing and arrays.
- Matplotlib: Data visualization and plotting.
- Seaborn: Advanced statistical data visualization.
- Scikit-Learn: Machine learning algorithms and tools.
- TensorFlow: Deep learning framework by Google.
- Keras: High-level neural network API.
- NLTK: Natural language processing toolkit.
- SQLite: Lightweight database for local storage.
- PostgreSQL: Advanced relational database system.
- MongoDB: NoSQL database for unstructured data.
- Docker: Containerization for application deployment.
- Kubernetes: Container orchestration and management.
- CI/CD: Continuous integration and deployment practices.
- Jupyter Notebook: Interactive coding environment for data science.
- Git: Version control for code management.
- AWS: Cloud services for scalable solutions.
Data Science Course With AI Summary
The Data Science Course with AI is designed to provide a comprehensive understanding of data analysis, machine learning, and artificial intelligence. You will learn to handle and analyze large datasets, build predictive models, and implement AI-driven solutions. The course covers essential topics including statistical analysis, data visualization, and advanced machine learning algorithms. By integrating hands-on projects and real-world applications, you will gain practical experience in data science and AI. Upon completion, you will be equipped with the skills needed to excel in data-driven roles and earn a certification that opens doors to diverse career opportunities in the data science and AI fields.