DATA SCIENCE

– Excel Fundamentals
– Excel for Data Analytics
– Data Visualization with Excel
– Excel Power Tools (Power Query, Power Pivot)
– Classification Problems Using Excel
– Information Measures in Excel
– Regression Problems Using Excel

• AI & Tools Covered
  – Microsoft Copilot for Excel (formula generation, insights)
  – Excel Analyze Data (AI-driven insights)
  – ChatGPT for Excel logic & automation support
• Hands-on Outcomes
  – Automated dashboards
  – Business KPI analysis
  – Predictive modeling using Excel

– Introduction to Relational Databases
– Data Integration and ETL Concepts
– SQL Fundamentals
– Advanced SQL Techniques
– Mathematical Foundations for Analytics
– Basic Statistics
– Statistical Methods & Hypothesis Testing

• AI & Tools Covered
  – ChatGPT for SQL query optimization
  – SQL AI Assistants (Azure Data Studio AI, pgAdmin hints)
  -Wolfram Alpha for statistical reasoning
• Hands-on Outcomes
  – Complex SQL analytics queries
  – Statistical inference reports

– Cloud Computing for Data Science
– Google Colab & Kaggle Workbooks
– Python Programming Basics
– Python Essentials
– NumPy for Numerical Computing
– Pandas for Data Manipulation
– Data Cleaning & Feature Engineering
– Exploratory Data Analysis (EDA)

• AI & Tools Covered
  – ChatGPT / GitHub Copilot for Python coding
  – Kaggle Notebooks AI Assistant
  – Pandas AI
  – Jupyter AI
• Hands-on Outcomes
  – Cleaned datasets
  – Automated EDA pipelines

– Visualization Fundamentals
– Python Visualization Libraries (Matplotlib, Seaborn, Plotly)
– Advanced Data Visualization Techniques
– Storytelling with Data
– Power BI Essentials
– Tableau Essentials

• AI & Tools Covered
  – Power BI Copilot
  – Tableau GPT / Ask Data
  – ChatGPT for visualization narratives
• Hands-on Outcomes
  – Interactive dashboards
  – Executive-ready visual reports

– Machine Learning – Supervised Learning
– Machine Learning Fundamentals
– Regression Algorithms
– Classification Algorithms
– Model Evaluation Metrics

• AI & Tools Covered
  – Scikit-learn
  – AutoML (Google AutoML, H2O.ai)
  – ChatGPT for feature engineering & evaluation
• Hands-on Outcomes
  – End-to-end ML pipelines
  – Business prediction use cases

– Clustering Techniques
– Dimensionality Reduction
– Recommender Systems
– Time Series Forecasting

• AI & Tools Covered
  – Scikit-learn
  – Facebook Prophet
  – PyCaret
• Hands-on Outcomes
  – Customer segmentation models
  – Forecasting systems

– Text Mining & Natural Language Processing
– Text Preprocessing
– Feature Engineering
– Predictive Modeling with Text
– NLP with NLTK & Scikit-learn

• AI & Tools Covered
  – SpaCy
  – Hugging Face Transformers
  – ChatGPT for text analytics workflows
• Hands-on Outcomes
  – Sentiment analysis systems
  – Text classification engines

– Artificial Intelligence Overview
– Deep Learning Fundamentals
– Artificial Neural Networks
– MLOps Fundamentals
– Cloud Deployment of ML Models

• AI & Tools Covered
  – TensorFlow / PyTorch
  – MLflow
  – Docker
  – FastAPI
• Hands-on Outcomes
  – Deployed ML APIs
  – Model lifecycle tracking

– LLM Fundamentals
– Prompt Engineering Patterns
– Tool & Function Calling
– Retrieval Augmented Generation (RAG)
– Vector Databases & Semantic Search
– Parameter Efficient Fine-Tuning (LoRA, Adapters)
– GenAI Safety, Bias & Alignment

• AI & Tools Covered
  – OpenAI / Azure OpenAI
  – LangChain / LlamaIndex
  – FAISS / Chroma / pgvector
  – Hugging Face
• Hands-on Outcomes
  – Domain-specific AI assistants
  – RAG-powered applications

– LLM Fundamentals
– Prompt Engineering Patterns
– Tool & Function Calling
– Retrieval Augmented Generation (RAG)
– Vector Databases & Semantic Search
– Parameter Efficient Fine-Tuning (LoRA, Adapters)
– GenAI Safety, Bias & Alignment

• AI & Tools Covered
  – OpenAI / Azure OpenAI
  – LangChain / LlamaIndex
  – FAISS / Chroma / pgvector
  – Hugging Face
• Hands-on Outcomes
  – Domain-specific AI assistants
  – RAG-powered applications

– AI Microservices Architecture
– Orchestration with Modern AI Frameworks
– Monitoring & Observability for ML/LLMs
– CI/CD for ML Pipelines
– Model Governance & Compliance

• AI & Tools Covered
  – Kubernetes
  – Airflow
  – Prometheus & Grafana
  – Weights & Biases
• Hands-on Outcomes
  – Production-grade AI pipelines
  – Continuous monitoring systems

– Advanced SQL & Data Modeling
– Warehouse vs Lakehouse Architectures
– Batch & Streaming Pipelines
– Workflow Orchestration
– Big Data & Distributed ML

• AI & Tools Covered
  – Apache Spark
  – Databricks
  – Kafka (intro)
  – Cloud GPU Environments (AWS/GCP/Azure)
• Hands-on Outcomes
  – Scalable data pipelines
  – Big data analytics systems

A:If you are interested and can dedicate a few hours to data science course in Kochi, you can easily achieve certification in data science. It combines computer science, math and  statistics, as well as domain knowledge to find insights from data. Even though knowledge in these areas are helpful, it is not mandatory.

A:Some of the languages used in data science are Python, R and SQL. You can learn the basics of Data Science with RICE and languages you need to learn to grow in this field. Note that before you enrol in Data Science Training, you must have basic programming skills to start a career in data science.

A:Data science offers a lot of opportunities both in marketing and sales by allowing them insights into customer behavior, preferences, and trends. It identifies potential leads, customizes advertising campaigns, enhances pricing strategies and helps in forecasting sales. Enrol with Techmindz that offers you the best Data Science Course to boost your career.

A: Yes. As the leading Data Science Institute, we will provide you a certificate upon completion.

A:Yes, we provide both online course and offline course for Data Analytics in Kochi so you can choose the course program as per your requirements.

Data scientists is one of the leading job profiles for various industries such as finance, healthcare, retail, technology, etc. Join our customized Machine Learning course in Kochi with Techmindz.