Kickstart your career with our Data Science training in Surat, designed for IT students and beginners. Learn everything from fundamentals to advanced topics like statistics, data visualization, machine learning, deep learning, artificial intelligence, and big data tools with Python, Pandas, NumPy, Matplotlib, Scikit-learn, and TensorFlow.
Our expert-led course focuses on real-world projects using Jupyter Notebooks, ensuring you gain practical skills to stand out in today’s data-driven job market. Whether you’re new to analytics or aiming to upskill, this course is the perfect stepping stone to becoming a proficient Data Scientist.
Data Science Training Schedule
10% OFF , Save ₹5,000
Easy to Learn, Powerful to Apply
Data Science is at the heart of innovation across industries today. With our certification program, you’ll master essential tools and techniques including Python, SQL, machine learning, statistics, and data visualization. From building predictive models to uncovering hidden patterns in data, you’ll gain the skills to solve real-world problems and drive smarter decisions. Whether you’re aiming for roles in AI, machine learning, or advanced analytics, this certification opens the door to high-impact careers in the fast-growing field of data science.
High Demand & Job-Ready Skills
Data scientists are in high demand in around the world. Through this certification, you’ll build hands-on expertise in Python, SQL, machine learning, statistics, and data visualization. From developing predictive models to extracting meaningful insights from complex data, you’ll gain the job-ready skills needed to tackle real-world challenges and make data-driven decisions — giving you a competitive edge in today’s rapidly evolving tech landscape.
Strong Community Support and Resources
Data Science is powered by a vibrant and ever-growing global community that shares tools, frameworks, research, and real-world solutions. By enrolling in a certification course, you’ll benefit from structured learning while tapping into the shared knowledge of data scientists, machine learning engineers, and industry experts worldwide. This ecosystem provides access to high-quality tutorials, open-source libraries, datasets, case studies, and active discussion forums — making your learning experience more hands-on, collaborative, and future-ready.
Data Science Course Syllabus
What is Python, and why use it?
Installing Python and using an IDE (IDLE / VS Code)
Writing and running the first Python program
Python syntax, indentation, and comments.
Variables & data types
Input/Output (input(), print())
Operators (arithmetic, comparison, logical, assignment)
Type conversion & casting
If, else, elif
Nested if
Loops: for, while
Break, continue, pass
Strings & string functions
Lists, Tuples, Sets, Dictionaries
List comprehensions
Defining functions, return values
Arguments (default, keyword, variable-length)
Lambda functions
Importing and creating modules
Using built-in modules (math, random, datetime)
Opening, reading, and writing files
Working with CSV & JSON files
Exception handling (try, except, finally, raise)
Classes and objects
Constructors & destructors
Inheritance, polymorphism, encapsulation
Method overriding
What is Data Science ?
Why is Data Science important ?
Data Science workflow
Roles in Data Science
Types of data
Handling Missing data & duplicates
Data formatting & feature encoding
Introduction to APIs & web scraping
Descriptive statistics (mean, median, mode, variance, correlation)
Visualization techniques (Histograms, boxplots, scatter plots, heatmaps)
Finding trends and insight
What is Machine Learning?
Types of ML: Supervised, Unsupervised, Reinforcement
ML in real life (recommendations, fraud detection, NLP, CV)
Model training, testing, and evaluation (accuracy, precision, recall, F1-score)
Natural Language Processing (NLP basics)
Time Series Analysis (forecasting trends)
Introduction to Deep Learning (Neural Networks)
Advanced plots with Seaborn & Matplotlib
Interactive dashboards (Power BI, Tableau, or Plotly)
Turning insights into stories for business decisions
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