Job Oriented Data Science Course in Hyderabad
We at RVConsultings provide the best Data Analyst course. RV Consultings has smartly designed data analyst training to help our students start promising careers.
Why Choose Us
At Rv Consultings, we're committed to empowering individuals with the skills and knowledge to excel in the world of Data Science. Our effective data science course training program is designed to equip you with the latest industry best practices and hands-on experience.
Modules You Learn In Data Analyst Course
Module 1
Introduction to Data Science and AI (3 Classes)
- Class 1: Overview of Data Science and AI
- History, Key Concepts, and Applications
- Importance in Various Industries
- Class 2: Getting Started with Data Science
- Tools and Technologies
- Setting Up the Environment (Python, Jupyter)
- Class 3: Data Science Workflow
- Data Collection, Cleaning, Analysis, Modeling, and Deployment
Module 2
Programming for Data Science (5 Classes)
- Class 4: Python for Data Science
- Basic Syntax, Data Types, and Control Structures
- Class 5: Advanced Python for Data Science
- Libraries (NumPy, Pandas)
- Class 6: Data Manipulation with Pandas
- DataFrames, Data Cleaning, Data Transformation
- Class 7: Data Visualization with Matplotlib and Seaborn
- Plotting Graphs and Charts
- Class 8: Introduction to SQL
- Basics of SQL, Queries, Joins
Module 3
Statistics and Mathematics for Data Science (5 Classes)
- Class 9: Descriptive Statistics
- Mean, Median, Mode, Variance, Standard Deviation
- Class 10: Probability Theory
- Basic Probability, Distributions, Bayes’ Theorem
- Class 11: Inferential Statistics
- Hypothesis Testing, Confidence Intervals
- Class 12: Linear Algebra
- Vectors, Matrices, Matrix Operations
- Class 13: Calculus for Machine Learning
- Derivatives, Integrals, Gradients
Module 4
Data Engineering (5 Classes)
- Class 14: Introduction to Data Engineering
- ETL Processes, Data Pipelines
- Class 15: Working with Big Data Tools
- Hadoop, Spark
- Class 16: Cloud Platforms for Data Engineering
- AWS, Azure, GCP
- Class 17: Data Warehousing
- Concepts, Tools (Snowflake, Redshift)
- Class 18: Data Lakes
- Architecture, Implementation
Module 5
Machine Learning (6 Classes)
- Class 19: Introduction to Machine Learning
- Supervised vs Unsupervised Learning
- Class 20: Regression Algorithms
- Linear Regression, Polynomial Regression
- Class 21: Classification Algorithms
- Logistic Regression, Decision Trees, Random Forests
- Class 22: Clustering Algorithms
- K-Means, Hierarchical Clustering
- Class 23: Dimensionality Reduction
- PCA, LDA
- Class 24: Model Evaluation and Selection
- Cross-Validation, Metrics (Accuracy, Precision, Recall, F1-Score)
Module 6
Deep Learning (5 Classes)
- Class 25: Introduction to Neural Networks
- Perceptron, Activation Functions
- Class 26: Deep Learning Frameworks
- TensorFlow, Keras, PyTorch
- Class 27: Convolutional Neural Networks (CNNs)
- Image Processing, Applications
- Class 28: Recurrent Neural Networks (RNNs)
- Sequence Modeling, LSTM, GRU
- Class 29: Generative Adversarial Networks (GANs)
- Concept, Applications
Module 7
Natural Language Processing (NLP) (5 Classes)
- Class 30: Introduction to NLP
- Text Preprocessing, Tokenization, Stemming
- Class 31: NLP with Python Libraries
- NLTK, SpaCy
- Class 32: Sentiment Analysis and Text Classification
- Class 33: Topic Modeling
- LDA, Latent Semantic Analysis
- Class 34: Advanced NLP Techniques
- Transformers, BERT, GPT
Module 8
AI and Machine Learning in Practice (5 Classes)
- Class 35: AI in Healthcare
- Use Cases, Applications
- Class 36: AI in Finance
- Use Cases, Applications
- Class 37: AI in Retail and E-commerce
- Use Cases, Applications
- Class 38: Building AI Solutions
- End-to-End Project Implementation
- Class 39: AI Ethics and Governance
- Responsible AI, Ethical Considerations
Module 9
Data Science Project Management (3 Classes)
- Class 40: Agile Project Management
- Scrum, Kanban
- Class 41: Documentation and Reporting
- Best Practices for Data Science Projects
- Class 42: Collaboration Tools
- Git, GitHub, Jira
Module 10
Practical Applications and Capstone Projects (5 Classes)
- Class 43: Real-World Data Science Project Planning
- Defining Project Objectives, Data Collection
- Class 44: Project Execution
- Data Cleaning, Exploration, Modeling
- Class 45: Deploying Data Science Models
- Using Flask, Docker
- Class 46: Performance Monitoring and Optimization
- Class 47: Capstone Project Presentation
Module 11
Career Preparation (3 Classes)
- Class 48: Interview Preparation
- Common Data Science and AI Interview Questions, Mock Interviews
- Class 49: Portfolio Building
- Creating and Showcasing Projects on GitHub
- Class 50: Resume Writing
- Tailoring Resumes for Data Science and AI Roles
Testimonials
I've taken several testing courses before, but RV Consultings has been the best by far. The trainers have real-world experience and share practical tips that I can apply immediately. I've already seen a significant improvement in my testing efficiency.
Affordable Data Analyst Course Fees
Our Data Analyst training provides exceptional value for the cost. You'll receive expert instruction, hands-on experience, and dedicated support to help you achieve your career goals.