ELINAUT

E L I N A U T

Address
Vennala puthiya Road Thykauv jun, opp. Clearway Appt, Arakkakadavu, Kakkanad, Kerala 682028
Email
mail@elinaut.com
Contact
+91 9567863498

Select Curriculum:

Introduction to Data Science - 1-month Intermediate Data Science - 3 Month Advanced Data Science - 6 month

Target Audience

Beginners with basic programming knowledge (preferably Python).

Objective

Understand the fundamentals of data science, data handling, and basic analysis techniques.

What You'll Learn

80 hours of comprehensive training

20 hours per week

Hands-on practical experience

Industry-relevant curriculum

Expert instructors

Week 1: Fundamentals of Data Science

Introduction to Data Science (4 hours)
- Definition, scope, and applications (business, healthcare, finance, etc.).
- Data science lifecycle: Data collection, cleaning, analysis, visualization.
Python for Data Science (6 hours)
- Python basics: Variables, loops, functions.
- Libraries: NumPy, Pandas for data manipulation.
Data Fundamentals (6 hours)
- Types of data: Structured, unstructured, big data.
- Introduction to databases and SQL basics.
Lab: Setting up Python environment and exploring datasets with Pandas (4 hours).

Week 2: Data Preprocessing and Exploration

Data Cleaning and Preprocessing (6 hours)
- Handling missing values, outliers, and data normalization.
- Feature engineering basics.
Exploratory Data Analysis (EDA) (8 hours)
- Descriptive statistics: Mean, median, variance.
- Data visualization with Matplotlib and Seaborn.
Lab: Performing EDA on a sample dataset (6 hours).

Week 3: Basic Statistics and Machine Learning

Statistics for Data Science (6 hours)
- Probability distributions, hypothesis testing.
- Correlation and regression basics.
Introduction to Machine Learning (6 hours)
- Supervised vs. unsupervised learning.
- Simple models: Linear regression, k-NN.
Lab: Building a basic regression model using scikit-learn (8 hours).

Week 4: Data Visualization and Projects

Advanced Visualization (6 hours)
- Interactive plots with Plotly.
- Dashboard basics with Streamlit.
Introduction to SQL (6 hours)
- Querying databases for data extraction.
- Joining tables and aggregating data.
Lab: Creating visualizations and a simple dashboard (6 hours).
Capstone Project: Analyze a dataset and present insights (2 hours).

Prerequisites

Basic programming knowledge for the 1-month course; completion of prior modules or equivalent for 3-month and 6-month courses.

Tools & Software

Python

Jupyter

scikit-learn

TensorFlow

Spark

SQL

AWS/GCP.

Delivery Mode

Combination of lectures, hands-on labs, and project work.

Assessment

Weekly quizzes, lab assignments, and capstone projects.

Certification

Certificate of completion for each module; preparation for industry-recognized certifications in the 6-month course.

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Duration 80 hours
Weekly 20 hours
Level All Levels

Available Curricula

Introduction to Data Science - 1-month

Duration: 1-month

Selected

Intermediate Data Science - 3 Month

Duration: 3-month

Select

Advanced Data Science - 6 month

Duration: 6-month

Select

Course Highlights

Expert instructors with industry experience
Hands-on projects and real-world applications
Flexible learning schedule
Placement assistance

Diploma in Data Science

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