Best Data Science Course in Shimla with 100% Practical Training & Placement Assistance
Enroll in the Data Science Course at IICEA Shimla and learn Python, statistics, data analysis, machine learning, data visualization and practical data science techniques.
Learn through practical datasets, Python programming, machine learning exercises, data visualization and industry-oriented Data Science projects.
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Data Science Course Overview
The Data Science Course in Shimla at IICEA is designed for students, graduates, beginners, programmers, data enthusiasts and working professionals who want to develop practical Data Science skills.
You will learn Python programming, statistics, NumPy, Pandas, data cleaning, exploratory data analysis, data visualization, SQL, machine learning and predictive analytics.
The training focuses on practical datasets, data analysis, machine learning models, visualization, live projects and industry-oriented Data Science workflows.
Skills You'll Gain
Python for Data Science
Learn Python programming and the concepts required for practical Data Science.
Statistics
Understand statistics and probability concepts used in data analysis and modelling.
NumPy & Pandas
Work with numerical data, DataFrames, data cleaning and data manipulation.
SQL
Query databases, retrieve information and prepare data for analysis.
Data Visualization
Create charts and visualizations to understand and communicate data insights.
Machine Learning
Learn machine learning algorithms, model training and predictive analysis.
Exploratory Data Analysis
Explore datasets, identify patterns and generate meaningful data-driven insights.
Predictive Analytics
Develop predictive models and apply Data Science techniques to real-world data.
Syllabus
- Introduction to Data Science
- Data Science Lifecycle
- Role of a Data Scientist
- Types of Data
- Data Science Applications
- Data-Driven Decision Making
- Real-World Data Science Use Cases
- Python Fundamentals
- Variables & Data Types
- Operators
- Conditional Statements
- Loops
- Functions
- Lists, Tuples & Dictionaries
- Sets
- Object-Oriented Programming Basics
- File Handling
- Exception Handling
- NumPy Introduction
- Arrays
- Array Indexing & Slicing
- Array Operations
- Mathematical Operations
- Statistical Functions
- Data Transformation
- Practical NumPy Exercises
- Pandas Introduction
- Series & DataFrames
- Importing Datasets
- Data Inspection
- Data Cleaning
- Missing Data Handling
- Data Filtering
- Data Transformation
- Grouping & Aggregation
- Data Analysis Exercises
- Introduction to Statistics
- Population & Sample
- Mean, Median & Mode
- Range & Variance
- Standard Deviation
- Probability Fundamentals
- Distributions
- Correlation
- Statistical Interpretation
- Database Fundamentals
- SQL Introduction
- Creating Databases & Tables
- SELECT Queries
- WHERE Conditions
- Sorting & Filtering
- GROUP BY & Aggregation
- Joins
- Subqueries
- Data Extraction for Analysis
- Exploratory Data Analysis
- Data Exploration
- Matplotlib
- Seaborn
- Charts & Graphs
- Bar Charts
- Line Charts
- Scatter Plots
- Heatmaps
- Data Storytelling
- Introduction to Machine Learning
- Machine Learning Workflow
- Supervised Learning
- Unsupervised Learning
- Features & Labels
- Training & Testing Data
- Model Training
- Model Evaluation
- Linear Regression
- Multiple Linear Regression
- Logistic Regression
- Decision Trees
- Random Forest
- K-Nearest Neighbors
- Support Vector Machines
- K-Means Clustering
- Model Comparison
- Scikit-Learn Introduction
- Data Preprocessing
- Feature Selection
- Feature Scaling
- Train-Test Split
- Model Training
- Model Prediction
- Model Evaluation
- Cross Validation Basics
- Practical Machine Learning Projects
- Predictive Analytics Fundamentals
- Regression Analysis
- Classification
- Forecasting Concepts
- Model Interpretation
- Prediction & Decision Making
- Business Data Analysis
- Predictive Analytics Project
- Jupyter Notebook
- Google Colab
- Python Data Science Libraries
- Data Science Workflow
- Project Documentation
- Git & GitHub Basics
- Data Science Portfolio Development
- Resume Preparation
- Interview Preparation
- Data Cleaning Project
- Exploratory Data Analysis Project
- Data Visualization Project
- SQL Data Analysis Project
- Machine Learning Project
- Predictive Analytics Project
- Final Data Science Portfolio Project
- Project Presentation
- Industrial Training
Professional Certification
Build your professional profile with practical Data Science skills, Python programming, machine learning projects, data analysis and course completion certification.
Earn a Professional Certificate & Stand Out.
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Why Choose Us?
Job-Focused Training
Practical Data Science training focused on Python, data analysis and machine learning.
Practical Data Projects
Work with datasets and build practical Data Science and analytics projects.
80% Practical & 20% Theory
Learn by analysing data, writing Python programs and building machine learning models.
Personalized Mentorship
Individual guidance and doubt-solving support throughout the training.
Industry Tools & Technologies
Learn Python, SQL, NumPy, Pandas, visualization and machine learning tools.
Certification
Get course completion certification after successful completion.
Career Preparation
Build projects, portfolio skills, interview readiness and career confidence.
Job Assistance
Get career guidance, interview preparation and placement assistance.
Contact Us
sunny villa, near st. Xavier school, North Oak, Sanjauli, Shimla, Himachal Pradesh 171006 +91 62307 00689
Monday to Saturday – 9:00 AM to 7:00 PM
+91 62307 00689
iiceaorg@gmail.com
FAQs
Students, graduates, beginners, programmers, data enthusiasts and working professionals can join the Data Science Course.
No. The course covers Python fundamentals before moving into Data Science, statistics and machine learning.
The course covers Python, NumPy, Pandas, SQL, Matplotlib, Seaborn, Scikit-Learn, Jupyter Notebook, Google Colab and machine learning concepts.
Yes. The course includes practical datasets, Python exercises, data analysis, visualization, machine learning and project work.
Yes. Students work on practical data analysis, visualization, SQL, machine learning and predictive analytics projects.
IICE provides placement assistance, career guidance and interview preparation support to eligible students.
Yes. Students receive a course completion certificate after successfully completing the Data Science training.
