Data Science Course with Placement Support
Master Python, SQL, Machine Learning, and Deep Learning.
Build predictive models and launch your career in AI.
Why Data Science?
Data is the new oil. Companies need experts who can refine it into value.
Comprehensive Stack
We cover everything: Statistics for theory, Python for coding, SQL for data retrieval, Tableau/PowerBI for visualization, and Scikit-Learn/TensorFlow for ML/AI.
Math Foundation
We don't just teach code. We teach the Mathematics (Statistics, Linear Algebra, Calculus) behind the algorithms so you understand "Why" it works.
Real World Data
Work on messy, real-world datasets. Learn data cleaning, imputation, and feature engineering techniques used in the industry.
Project Portfolio
By the end of the course, you will have a GitHub portfolio with 5+ end-to-end projects (EDA, Regression, Classification, Clustering, NLP).
The Data Science Curriculum
From simple Charts to complex Neural Networks.
Logic & Basics
- Problem Solving & Logic Building
- Introduction to Programming
- Python Basics for Data Science
- Git & Command Line Basics
Python Libraries
- Python Syntax & Data Types
- Control Statements & Functions
- NumPy (Numerical Computing)
- Pandas (Data Manipulation & Analysis)
- Data Cleaning & Preprocessing
Stats & Prob
- Linear Algebra Basics
- Probability
- Descriptive Statistics
- Inferential Statistics
- Hypothesis Testing
Viz Tools
- Matplotlib
- Seaborn
- Plotly
- Interactive Dashboards
- Storytelling with Data
EDA Techniques
- Data Inspection
- Handling Missing Values
- Outlier Detection
- Feature Engineering
- Data Transformation
ML Algorithms
- Introduction to ML
- Supervised Learning
- Regression Algorithms
- Classification Algorithms
- Unsupervised Learning
- Clustering
- Dimensionality Reduction
- Model Evaluation & Metrics
- Overfitting & Underfitting
Advanced ML
- Ensemble Methods (Random Forest, XGBoost)
- Feature Selection Techniques
- Hyperparameter Tuning
- Model Optimization
DL Basics
- Neural Networks Basics
- TensorFlow / PyTorch
- CNN (Computer Vision Basics)
- RNN / LSTM (Sequence Models)
NLP
- Text Preprocessing
- Sentiment Analysis
- Topic Modeling
- Transformers & LLM Basics
Big Data Stack
- SQL for Data Science
- NoSQL Overview
- Big Data Basics (Spark)
- Data Warehousing Concepts
MLOps
- Model Deployment (Flask / FastAPI)
- Docker Basics
- CI/CD for ML
- Monitoring ML Models
Cloud ML
- AWS / Azure / GCP for ML
- Using Cloud ML Services
Your 5-Month Journey to Success
A structured, intense, and outcome-oriented roadmap designed to take you from novice to professional.
Py & Stats
Python programming and Statistics for Data Science.
Data Analysis
Data Manipulation and Visualization with Pandas and Matplotlib.
Machine Learning
Supervised and Unsupervised learning algorithms.
Deep Learning
Neural Networks, CNNs for Image, and RNNs/LSTMs.
Career Prep
Portfolio building, GitHub profile, and Mock Interviews.
Master the Tools of the Trade
Get hands-on experience with the practical tools and platforms used by top engineering teams worldwide.
Jupyter
NotebooksTableau
VisualizationPowerBI
VisualizationGoogle Colab
Cloud NotebooksPandas
LibrarySlack
CommunicationJira
Project MgmtGitHub
Version ControlGit
Version ControlOpenAI
AI AssistantGemini
AI AssistantZoom
CommunicationReal World Case Studies
Apply your skills on real-world datasets. From data cleaning to deploying ML models.
Credit Card Fraud
Build a classification model (XGBoost, Random Forest) to detect fraudulent transactions in imbalanced data.
Stock Forecasting
Predict future stock prices using LSTM (Deep Learning) and ARIMA models.
Customer Segmentation
Group customers based on purchasing behavior using K-Means Clustering for targeted marketing.
Earn a Certificate that
Proves Your Expertise
Upon successful completion of the course and capstone project, you will receive an industry-recognized certification from Aideas Academy.
We Don't Just Teach.
We Get You Hired.
Resume Building
Craft a world-class resume that stands out. We help you highlight your skills and projects effectively.
- ATS Optimized
- Project Highlighting
- Keyword Strategy
Mock Interviews
Practice with industry experts. Get real-time feedback to crack technical and HR rounds with confidence.
- Technical Rounds
- HR Questions
- Confidence Building
Career Mentorship
1-on-1 guidance from seniors in top MNCs. Map out your career path and meaningful growth strategies.
- 1-on-1 Sessions
- Industry Insights
- Growth Roadmap
Job Alerts
Get exclusive access to our hiring network. We connect you directly with startups and MNCs hiring now.
- Exclusive Openings
- Direct Referrals
- Interview Scheduling
Don't Just Take Our Word.
See Their Offer Letters.
Join 1,200+ students who have transformed their careers with our Data Science program.
Arjun Mehta
I shifted from manual testing to Python development. The Django and API modules are very detailed. I built a complete E-commerce site which impressed my interviewers.
Priya Sharma
The combination of Python, SQL, and AWS in this course is perfect for Data Engineering roles. I use the concepts I learned here every single day at my job.
Vishal Singh
FastAPI coverage was excellent. I learned how to build high-performance APIs and handle async requests. The mock interviews helped me refine my technical answers.
Neha Patel
I had zero coding knowledge. They started with basic Python and took us to advanced frameworks. The mentorship and code reviews were very helpful.
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Frequently Asked Questions
Everything you need to know about the course and billing.
Is coding required?
What's difference between Data Analyst vs Scientist?
Do you cover Deep Learning/AI?
Do I need a strong Maths background?
Do you provide job support?
Future Proof Your Career
AI will not replace you. A person using AI will. Master Data Science today.