The best data science course in Bangalore teaches you the scientific methods, algorithms, processes & systems to extract knowledge & insights from structured & unstructured data. It combines elements of statistics, computer science, mathematics & domain expertise to analyze and interpret complex data sets.
The goal is to turn raw data into actionable insights that can drive business decisions, optimize processes & fuel innovation. This is why the demand for skilled data scientists continues to surge.
With vast applications spanning everything from ML & AI to business analytics & automation. Undertaking the best data science course in Bangalore is one of the best decisions to make.
In this blog, we’ll guide you through the best DS certification in Bengaluru. With it’s benefits, learning outcomes, curriculum & more.
Benefits of Data Science Certification in 2024
| Career advancement | High demand in job market | Increased earning potential |
| Industry credibility & recognition | Career flexibility & growth | Improved critical thinking |
| Enhanced creativity & innovation | Increased job security | Opportunities in AI & automation |
Best Data Science Course in Bangalore: Code & Debug
Offering the best Data Science course in Bangalore, Code & Debug has developed a comprehensive course. It’s designed for beginners, intermediate as well as experienced learners.
Get hands-on experience on DS fundamentals with Python, statistics, deep learning & more. All while solving real-life problems.
Become an expert in just 4 months & get ready to crack coding interviews with ease.
Also read about the best Python training in Bangalore.
Best Data Science Training in Bangalore: Learning Outcomes
| Master DS Concepts | Master Data Wrangling & Statistics |
| Industry-aligned Curriculum | Hands-on Learning on Real-World Problems |
| Learn Deep Learning & NLP | Learn Relational Databases & ML |
| Industry-leading Expert Instructors | Interview Preparation |
| Efficient Problem Solving | Project-based Learning with Real-World Applications |
Best DS Certification in Bengaluru: Course Curriculum
At Code & Debug, we believe in delivering a well-rounded, thorough learning experience. One that doesn’t just hover upon topics but covers every crucial aspect of learning DS.
Our syllabus is designed to take you from foundational concepts to advanced problem-solving techniques. Here’s what you’ll be learning:
Module – 1
Python – Basic to Advance
- Python Keywords and identifiers
- Comments, indentation and statements
- Variables and data types in Python
- Operators
- Control flow: if, else, elif
- Control flow: while loop, for loop, break and continue
- Strings
- Lists, Lists comprehension
- Tuples
- Sets
- Dictionary, Dictionary Comprehension
- In-built Functions and Methods and types of function arguments
- Class hands-on: 8+ Programs to be covered in the functions, Lambda, modules, Generators, and Packages class
- Decorators
- Map, reduce, filter functions.
- OOPs in Python.
- Errors and Exception Handling.
- File Handling
Module – 2
Numerical Coding with Python
- Mastering Data Wrangling
- Advanced Data Wrangling Concepts
- Data Wrangling on Different Data Formats
- Data Visualization with Matplotlib & Seaborn
- Data Vizualization Tips & Variable Analysis
- Exploratory Data Analysis | Ecommerce Case Study
- Data Modelling via APIs
- Interactive Visuals with Plotly
- Streamlit Dashboards with dynamic Interactions
Module – 3
Relational Database
- Dealing With Multiple Tables
- Advanced SQL Joins
- Type Casting & Math Functions
- DateTime Functions
- String Functions
- Window Functions
- Complex queries using CTE & Connecting with Azure Database
- Data Exploration With SQL & Python
- Database Management & Schema Design
Module – 4 (Stats)
Stats Basics
- Intro to basic stats terms
- Types of statistics
- Types of data
- Levels of Measurement
- Measure of Central Tendency
- Measure of Dispersion
- Random Variables
- Set
- Skewness
- Covariance and Correlation
Stats Advance
- Prob density/distribution function
- Types of the prob distribution
- Binomial Distribution
- Prob Density function and Mass Function
- Cumulative Density Function
- Examples of Normal Distribution
- Bernoulii Distribution
- Cumulative Density Function
- Examples Of Normal Distribution
- Bernoulli Distribution
- Uniform Distribution
- Z Stats
- Central Limit Theorem
- Estimation
- A Hypothesis
- Hypothesis Testing’s Mechanism
- P-Value
- T-Stats
- Student T Distribution
- T-Stats Vs. Z-Stats: Overview
- When To Use A T-Tests Vs. Z-Tests
- Type 1 & Type 2 Error
- Bayes Statistics (Bayes Theorem)
- Confidence Interval(Ci)
- Confidence Intervals And The Margin Of Error
- Interpreting Confidence Levels And Confidence Intervals
- Chi-Square Test
- Chi-Square Distribution Using Python
- Chi-Square For Goodness Of Fit Test
- When To Use Which Statistical Distribution?
- Analysis Of Variance (ANOVA)
- Assumptions To Use Anova
- Anova Three Type
- Partitioning Of Variance In The Anova
- Calculating Using Python
- F-Distribution
- F-Test (Variance Ratio Test)
- Determining The Values Of F
- F Distribution Using Python
Module – 5 (Machine Learning)
Supervised Learning
- Linear Regression Analysis
- Decision Tree
- Random Forest
- K-Nearest Neighbour
- Support Vector Machine
- Logistic Regression
- Naive Bayes
Unsupervised Learning
- Clustering K means and Hierarchical
- Principle Component Analysis
- Recommendation System
Time Series & Ensemble Techniques
- Boosting | Gradient
- Boosting | XGBoost
- Understanding Time Series
- Arima
Module – 6
Deep Learning
- Machine Learning Vs Deep Learning
- Tensorflow | Keras | Pytorch
- Overview Caffe and Theano
- Artificial Neural Networks (ANN)
- Recurrent Neural Networks
- Convolutional Neural Networks
- Autoencoders and Boltzmann Machine
- Natural Language Processing
- NLP & Text Analytics
- Text Data Pre-processing and Cleaning
- Information Retrieval Systems, Topic Modeling
- Distance Algorithms and Entity Extractions Reinforcement Learning
- Introduction to RL
- Open AI
- RL Techniques and Methods
- Deep Q- Learning Computer Vision
- Image Processing
- Open CV
- Object Detection
What Our Students Say?
You have made learning DS, the least complex for beginners like me. Loved your way of teaching & explaining.
Parv Singhai
The material was well-articulated & thanks to your clear explanations, my understanding of the basics has improved. Appreciate your constant availability & support throughout the course!
Siddesh dagwal
The teaching style made complex topics easy to understand. Solved many questions on my own just by listening to your lectures.
Mohammed Ghouse Shaik
Why Code & Debug for DS Training in Bangalore?
| Live Interactive Training | Everyday Doubt Sessions |
| Weekly Tests | Daily Assignments |
| FAANG-Level Questions | Resume Building |
| LinkedIn and X Building | Career Support |
FAQs
I have no prior programming experience. Can I still register for classes?
Certainly! The classes are beginner-friendly and tailored to guide you from scratch. So, there is no need to know anything about coding beforehand.
Is it a live class or a pre-recorded course?
It’s a live class, allowing real-time interaction with instructors and solutions to leetcode questions for logic buildup.
What if I miss a live session? Can I catch up?
Yes, recordings will be available for missed sessions. All the recordings of LIVE classes will be available.
Is there a refund available?
Yes, a refund is possible within 14 days of the class starting date. No questions asked.
Do I need any prerequisites before starting the classes?
No prerequisites needed. The class will start from the basics and will go till advance.
