Unlock the World of Data Science with ENCODE-IT’s Data Science with Python Course

Data science is one of the most sought-after skills in today's technology-driven world. With its ability
to unlock insights from complex data, it has become a cornerstone for businesses across industries.
Python has emerged as one of the most powerful and versatile languages for data science due to its
simplicity, extensive libraries, and strong community support. Whether you're looking to start a
career in data science or expand your skill set, ENCODE-IT's Data Science with Python course will
provide you with the essential knowledge and hands-on experience to excel in this growing field.
This course takes you on a comprehensive journey through the core concepts of data science using
Python. You’ll learn how to manipulate, analyze, and visualize data, build predictive models, and
deploy machine learning algorithms. By the end of the course, you will be equipped with all the tools
and techniques required to solve real-world data problems and make data-driven decisions.

Course Overview
Data Science with Python is a complete, hands-on program that will help you learn everything from
basic data manipulation to advanced machine learning techniques. You'll master Python
programming, understand how to work with large datasets, and apply machine learning models to
solve business problems. With a mix of theoretical understanding and practical application, this
course will prepare you for a successful career in the field of data science.

The course is structured to guide you through all stages of a data science project, including data
collection, cleaning, exploration, and building predictive models. Whether you are starting your
career in data science or looking to upskill, this course is designed to provide you with all the
necessary tools to succeed.

Salary Scale in India
Data science professionals in India are highly sought after, with a demand for individuals skilled in
Python continuing to grow. The salary range for entry-level data scientists typically starts at ₹6 lakh
to ₹12 lakh per year. As professionals gain experience, salaries can rise to ₹12 lakh to ₹20 lakh, and
for those with extensive expertise, ₹20 lakh to ₹30 lakh or more. This makes Python one of the most
valuable skills in data science, as many of the top companies in finance, technology, and healthcare
are actively hiring data scientists proficient in Python.

Placement Assistance & Certification in India
Upon successful completion of the Data Science with Python course, ENCODE-IT offers placement
assistance to help you land a role in the thriving data science job market. This includes job referrals,
resume building, and interview preparation. Additionally, you will receive a Certificate of
Completion that is recognized by leading companies in the industry. This certification validates your
skills and knowledge, enhancing your job prospects.

Course Curriculum

1. Introduction to Python for Data Science
o Introduction to Python Programming and Setup
o Python Basics: Variables, Data Types, Functions, and Loops
o Working with Python Libraries: Numpy, Pandas, Matplotlib, Seaborn
o File Handling: Reading and Writing Data
o Introduction to Jupyter Notebooks for Data Science

2. Data Collection and Preprocessing
o Importing and Exporting Data with Pandas
o Data Cleaning: Handling Missing Values, Duplicates, and Errors
o Data Transformation: Merging, Grouping, and Aggregating Data
o Data Normalization and Feature Scaling
o Feature Engineering and Encoding Categorical Variables
o Time Series Data Preprocessing

3. Exploratory Data Analysis (EDA)
o Understanding the Importance of EDA
o Data Visualization with Matplotlib and Seaborn
o Creating Histograms, Scatter Plots, Box Plots, and Heatmaps
o Statistical Summaries and Correlation Analysis
o Identifying Outliers and Anomalies in Data
o EDA for Time Series Data and Geospatial Data

4. Introduction to Machine Learning
o Introduction to Machine Learning Concepts and Algorithms
o Supervised vs. Unsupervised Learning
o The Machine Learning Pipeline: Data Preparation, Model Selection, Evaluation
o Introduction to Scikit-Learn for Machine Learning
o Basic Machine Learning Models: Linear Regression, K-Nearest Neighbors

5. Classification Algorithms
o Logistic Regression and its Applications
o Decision Trees and Random Forests
o Support Vector Machines (SVM) for Classification
o K-Means Clustering for Unsupervised Learning

o Model Evaluation: Accuracy, Precision, Recall, F1 Score
o Cross-Validation and Hyperparameter Tuning

6. Advanced Machine Learning Models
o Ensemble Methods: Random Forest, Gradient Boosting, AdaBoost
o Introduction to Neural Networks and Deep Learning
o Building Deep Learning Models using Keras
o Natural Language Processing (NLP) for Text Classification
o Implementing Recurrent Neural Networks (RNN) for Time Series Forecasting
o Model Optimization and Fine-Tuning Techniques

7. Time Series Analysis
o Introduction to Time Series Data
o Time Series Decomposition and Trend Analysis
o Autoregressive Models (AR), Moving Average (MA), ARIMA
o Forecasting with Time Series Data using Python
o Evaluating Time Series Models: RMSE, MAE, AIC, BIC
o Real-World Applications of Time Series Forecasting

8. Data Visualization and Reporting
o Advanced Data Visualization with Seaborn and Plotly
o Interactive Dashboards with Plotly Dash and Streamlit
o Visualizing Machine Learning Results and Model Performance
o Creating Business Intelligence Reports and Dashboards
o Reporting Insights with Data Visualizations for Decision Making

9. Real-World Data Science Projects
o Building a Customer Churn Prediction Model
o Sentiment Analysis on Social Media Data
o Stock Price Prediction using Machine Learning
o Recommendation System for E-commerce
o Fraud Detection and Anomaly Detection in Financial Transactions
o End-to-End Data Science Project: From Data Collection to Model Deployment

10. Final Project and Certification Exam
o Final Project: Develop a Data Science Solution for a Real-World Problem

o Complete Data Preprocessing, Modeling, and Evaluation
o Final Exam: Comprehensive Evaluation of Data Science and Python Skills
o Certification of Completion from ENCODE-IT and Job Placement Assistance

Key Features
 Tools & Platforms: Python, Jupyter Notebook, Numpy, Pandas, Matplotlib, Seaborn, Scikit-
Learn, Keras, TensorFlow, Plotly, Streamlit.
 Real-World Projects: Gain hands-on experience through real-world data science projects
such as sentiment analysis, stock price prediction, recommendation systems, and more.
 Expert Instructors: Learn from experienced instructors with deep industry knowledge,
offering insights into practical data science applications.
 Certification & Placement Support: Receive a Certificate of Completion and access to job
placement assistance, including resume building and interview preparation.
 Comprehensive Curriculum: From basic data manipulation to advanced machine learning,
this course covers all essential aspects of data science with Python.
 Career Advancement: Acquire the skills needed for high-paying roles in data science and
machine learning, with a strong focus on practical applications.

With ENCODE-IT’s Data Science with Python course, you’ll gain the skills, experience, and
confidence to embark on a successful career in data science. Start your data science journey today
and become an expert in one of the most in-demand fields in the tech industry!