Data Science Course
The Data Science course is designed by experts with extensive real-world experience in artificial intelligence, machine learning, deep learning, and a variety of other cutting-edge technologies.
Data Science Course Overview
The course focuses on giving you a thorough understanding of data science, including its applications and usage, R statistical computing, data manipulation, data visualisation, using descriptive and inferential statistics on the data, and much more. Furthermore, through working on actual projects and offering fixes for the issues, you’ll also learn how to do it. In a word, this online training in data science gives you complete confidence to attend interviews and work as a data scientist.
Course Curriculum
Introduction & Setup
- AI, ML, and Data Science overview
- Career paths & role differences
- Installing Python, VS Code, Jupyter, Git
- Git & Version Control
- Git init, add, commit, push, pull
- Branching & merging
- Connect to GitHub
- Python Basics I
- Variables, Data Types, Input/Output
- Python Basics II
- Lists, Tuples, Dictionaries, Sets
- Python Basics III
- Control Flow: if/else, for/while loops
- Functions & Modules
- Object-Oriented Programming (OOP)
- Classes, Objects, Inheritance, Encapsulation
- SQL Basics
- SELECT, FROM, WHERE, GROUP BY, ORDER BY
- SQL Joins & Aggregates
- INNER JOIN, LEFT JOIN, COUNT, SUM, AVG
- Math & Statistics Primer
- Mean, Median, Std, Probability Basics
- Linear Algebra & Calculus (Intro)
- NumPy for Scientific Computing
- Arrays, Vectorization, Math Operations
- Pandas I – DataFrames, Series, Reading CSV/Excel
- Pandas II – Data Cleaning, Missing Values, Filtering, Grouping
- Data Visualization I – Matplotlib & Seaborn: Line, Bar, Histogram
- Data Visualization II – Heatmaps, Pairplots, Visualization Principles
- Intro to Machine Learning –
- Supervised vs Unsupervised Learning
- ML Lifecycle Overview
- Scikit-Learn I – Linear/Logistic Regression & Evaluation
- Scikit-Learn II – Decision Trees, Random Forests, Hyperparameter Tuning
- Open Lab – Hands-on exercises, project prep
- Intro to Generative AI – Transformers, Attention Mechanism
- Large Language Models (LLMs) – GPT, LLaMA, BERT basics
- Prompt Engineering – Effective prompts, Zero-shot & Few-shot learning
- Retrieval-Augmented Generation (RAG) – Building basic chatbots on custom data
- Future of AI – AGI, AI Safety, Emerging Trends
- Big Data with Spark – RDD, DataFrames Basics
- Advanced SQL – Window Functions, CTEs
- BI Tools Intro – Power BI / Tableau Overview
- Data Storytelling – Visual Communication & Insight Presentation
- Advanced Statistics – A/B Testing, Hypothesis Testing, Correlation
- BI & Dashboarding – Interactive Dashboards in Power BI / Tableau
- Gen AI for Insights – Use LLMs to Summarize Data
- LLMs for Analytics – Automated Analysis with LLM APIs
- Mini Task – Automated Insight Generation
- Project Planning & EDA – Data Collection, Cleaning, Exploratory Data Analysis
- Model & Visualization – ML Model Build & Evaluation, BI Visualization for Presentation
- Final Presentation Prep – Storytelling Dashboards & Reports
- Full real-world project applying all skills:
- Big Data + SQL
- BI Dashboards & Data Storytelling
- Advanced Statistics for Insights
- Gen AI for Automated Analytics
- Feature Engineering (3h) – Encoding, Scaling, Outlier Handling
- Dimensionality Reduction (1.5h) – PCA, Variance & Feature Selection
- Clustering (3h) – KMeans, Hierarchical Clustering, Optimal K selection
- Advanced Statistics (3h) – ANOVA, Chi-Square, Regression Diagnostics
- Time Series Forecasting (4.5h) – ARIMA, Prophet, Seasonal Decomposition
- ETL/ELT Basics – Data Cleaning & Transformation Pipelines
- BI Reporting & Storytelling – Dashboards in Power BI / Tableau
- Automated Reporting – Scheduling & Insight Automation
- Full real-world project applying all advanced Data Science skills:
• Big Data + ML + BI Dashboard
• Gen AI for Automated Analytics
• Storytelling & Final Presentation
Hands-on Data Science Projects
Our data science training programme aspires to provide high-quality instruction that emphasises practical application of sound underlying knowledge on key issues. Students’ abilities will be enhanced and they will be able to complete real-world projects using the best practises thanks to exposure to use-cases and scenarios from the present industry.
Industry Statistics
Highlights
Sessions Led by Professionals
We provide 10 sessions, per session to 2 hours to complete the course.
Real-Life Case Studies
We have included countless examples and case studies from real life.
Assignments & Projects
You will receive assignments, study material, and projects after each session.
Exclusive Support
You will have access to our expert support in a specific time frame.
Completion Certificate
We will provide you a Course Completion Certificate once you have finished the course.
Job Assistance
Depending on your CTC, experience, and current skills, you will receive 100% job support.