Data Science Training & Certification
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.
Software Development Life Cycle
- Phases: Requirement, Design, Dev, Test
- Models: Waterfall, Agile, Scrum, DevOps
- Roles: BA, UI/UX, Dev, QA, DevOps
Intro to Data Science
- What is Data Science & Life Cycle
- Impact and Future of Data Science
Pre-Core Python
- Jupyter Notebook, Google Colab
- UNIX OS Basics
Python Intro
- Variables & Data Types
- Python Collections
Core Concepts
- Control Statements, Lists & Arrays
- Functions, Methods & Exceptions
- OOP Concepts & Database Communication
Python Libraries
- NumPy, Pandas, SciPy
- Matplotlib, Seaborn, Pillow
- TensorFlow Basics
Advanced Visualization
- Data Manipulation for Viz
- Histograms, Boxplots, Violin Plots
Power BI
- Data Extraction & Transformation
- Data Modeling & DAX
- Visualizations & Analytics
Statistics
- Population vs Sample
- Central Tendency & Dispersion
- Hypothesis Testing & Correlation
Probability
- Random Variables & Distributions
- Bayes Theorem & Maximum Likelihood
Linear Algebra
- Vectors & Matrices
- Eigenvalues & Eigenvectors
Data Structures
- Big O Notation
- Arrays, Linked Lists, Stacks, Queues
- Trees, Graphs & Sorting Algorithms
Regression
- Simple & Multiple Linear Regression
- Polynomial & Stepwise Regression
- Regularization (Lasso, Ridge, Elastic Net)
Classification
- Logistic Regression
- Decision Trees & Random Forests
- SVM & Kernel Trick
- Naive Bayes & KNN
Evaluation Metrics
- Confusion Matrix
- Accuracy, Precision, Recall, F1
- ROC Curve & AUC
Ensemble & Tuning
- Bagging & Boosting (XGBoost, LightGBM)
- Hyperparameter Tuning
- Feature Selection & Cross-Validation
Unsupervised
- K-Means & Hierarchical Clustering
- PCA & Dimensionality Reduction
Neural Networks
- ANNs, CNNs & RNNs
- Backpropagation & Activation Functions
- Computer Vision with OpenCV
Natural Language Processing
- Text Preprocessing (NLTK, SpaCy)
- Vectorization & Embeddings
- LSTMs & Sequence Tagging
GenAI Foundations
- GANs, VAEs & Transformers
- LLMs (GPT, Gemini, Claude)
- Hugging Face & Pre-trained Models
Prompt Engineering
- Principles & Best Practices
- Few-Shot & Chain-of-Thought
AI Agents & Integration
- Autonomous Agents vs Chatbots
- Tools, Function Calling & Orchestration
- Building AI-Driven UIs (React Integration)
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
CommunicationBuild Predictive Models
Don't just analyze the past. Predict the future.
Sales Forecasting
Use Time Series Analysis (ARIMA, Prophet) to predict future sales for a retail giant based on historical data.
Credit Risk Model
Build a classification model (Logistic Regression, Random Forest) to determine if a loan applicant is likely to default.
Sentiment Analysis
Perform NLP on Twitter/X data to analyze public sentiment about a brand or product launch.
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
"I was afraid of coding, but Aideas Academy taught Python in such a simple way. Now I build Machine Learning models for a Fintech company."
Related Courses
Expand your skills with these complementary certification programs.
Frequently Asked Questions
Is coding required?
Yes, Python is essential. However, we teach Python from the absolute basics, assuming zero prior coding knowledge.
What is the difference between Data Analyst vs Data Scientist?
Analysts focus on descriptive analytics (what happened). Scientists focus on predictive analytics (what will happen) using ML.
Do you cover Deep Learning?
Yes, we introduce Neural Networks and Deep Learning concepts towards the end of the course.
Future Proof Your Career
AI will not replace you. A person using AI will.