I had a nice experience at Creative-I-Lab. I liked the way the classes were conducted and the learning environment was comfortable. The teachers were supportive and I learned a lot during the course.
Data Science with Python
This course is designed to help you master essential Python programming concepts for Data Science, covering data operations, file handling, object-oriented programming, and key libraries such as Pandas, NumPy, and Matplotlib, while providing a comprehensive introduction to Machine Learning, Recommendation Systems, and core Data Science techniques for both beginners and professionals.
8 Lessons
EDA, Machine Learning & Deep Learning
Beginner Level
Python Programming & Math Foundations
ML & AI Stack
Pandas, Scikit-Learn, NLP & MLOps
Capstone Project
End-to-End Data Science Model Execution
What you’ll learn
Master core Python basics, mathematical foundations, and object-oriented programming for data workflows.
Conduct Exploratory Data Analysis (EDA) and data visualization using Matplotlib, Seaborn, and Pandas.
Implement Supervised and Unsupervised Machine Learning algorithms.
Apply Associate Rule Mining and Market Basket Analysis.
Understand neural network architectures including ANN, CNN, RNN, Reinforcement Learning (RL), and Transformers.
Perform Natural Language Processing (NLP) text processing and build Time Series Analysis (TSA) models using ARIMA and LSTM.
Gain introductory knowledge of operationalizing models with MLOps and complete a practical Capstone Project.
Skills you'll gain
Python Programming
Exploratory Data Analysis (EDA)
Supervised Learning
Unsupervised Learning
Market Basket Analysis
Deep Learning Architectures
Natural Language Processing (NLP)
Time Series Analysis (TSA)
MLOps
Tools you'll learn
Python
NumPy
Pandas
Matplotlib
Seaborn
Scikit-Learn
ARIMA
LSTM
This course covers end-to-end data processing, exploratory analysis, machine learning algorithms, deep learning neural networks, and MLOps fundamentals, giving you practical capabilities for real-world data science roles.
- Course Level: Beginner
- Total Duration: 45 Hours
- Total Curriculum: 8 Lessons
- Training Mode: Classroom (Offline)
- Prerequisites: Fundamental understanding of Computer Programming Languages.
- Target Audiences: AI and Machine Learning roles across research, engineering, product, data, consulting, and creative domains.
Curriculum
45 Hours
|
Beginner
What you’ll learn
Foundations of Python syntax, data operations, file handling, and core programming paradigms.
Skills you'll gain
Python Syntax
File Handling
Data Operations
What you’ll learn
Core mathematical and statistical concepts required for data science modeling and analysis.
Skills you'll gain
Applied Statistics
Linear Algebra
Probability
What you’ll learn
Graphical data representation using plotting libraries such as Matplotlib and Seaborn.
Skills you'll gain
Data Visualization
Matplotlib
Seaborn
What you’ll learn
Exploratory Data Analysis techniques for cleaning, wrangling, and discovering patterns in datasets.
Skills you'll gain
Exploratory Data Analysis
Data Cleaning
Data Preprocessing
What you’ll learn
Supervised
Build classification and regression models for labeled data.
Unsupervised
Implement clustering and dimensionality reduction techniques on unlabeled datasets.
Associate Rule Mining, Market basket Analysis
Discover relationships between products using association algorithms like Apriori.
Skills you'll gain
Supervised Learning
Regression
Classification
Unsupervised Learning
Clustering
Dimensionality Reduction
Association Rule Mining
Market Basket Analysis
What you’ll learn
Deep Learning: ANN, CNN, RNN, RL, Transformers
Overview of deep neural architectures, computer vision networks, sequential models, reinforcement learning, and transformers.
NLP: Basic Theory, Text Processing Techniques, Algorithms
Apply text cleaning, tokenization, feature extraction, and linguistic algorithms for NLP.
TSA: EDA for Time series, Algos: ARIMA, LSTM models
Perform time-series exploratory analysis and build forecasting models with ARIMA and LSTM networks.
Skills you'll gain
Artificial Neural Networks
Deep Learning
Transformers
Natural Language Processing
Text Preprocessing
NLP Algorithms
Time Series Forecasting
ARIMA
LSTM
What you’ll learn
Understand the principles of Machine Learning Operations (MLOps) for deployment, tracking, and model lifecycle management.
Skills you'll gain
MLOps Basics
Model Lifecycle Management
What you’ll learn
Integrate end-to-end Python programming, data analytics, ML modeling, and deployment concepts into a real-world project.
Skills you'll gain
End-to-End Data Science
Project Execution
Success Stories That Inspire
See how our students transformed their skills, built strong portfolios, and launched successful creative careers.
I joined Creative-I-Lab to improve my skills and I am happy with my decision. The classes are easy to understand and the trainer explains the topics with good examples. I also liked that the batches are small.
Sachin Ghule
I really liked learning at Creative-I-Lab. The teachers are friendly and explain everything in a simple way. The classes are easy to understand and the overall experience was good.
