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Data Science

Complete Overview Of The Course

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  • Total Slots : 60
  • Booked Slots : 45
  • Cost : Rs. 5999 - 11999
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Topics Covered

Python (Internals, do’s and don’ts) Architecture, Data Structure
  • Installation of Anaconda Prompt.
  • Jupyter Notebook-An Overview.
  • Shorcut Lkeys in Jupyter Notebook.
  • Data Types in Python
Python, Reading & Writing files in Python
  • Rules for Naming the Variables.
  • List, Tuple, Set, Dictionary.
  • Introduction to Files and Directories.
  • Introduction to the Command Prompt or
    Terminal Paths.
  • Text Files: Reading from a Text File (using
    with)
Loops and conditionals in python
  •  If, Elif, and Else Conditions
  • For and While Loops
Data Analysis , Manipulation with numpy
  • Machine Learning Libraries.
  • Numpy-Hands on.
Pandas Python data science package to manipulate, calculate and analyze data.
  •  “Pandas-Hands on”
Exploratory Data Visualization in Python with matplotlib
  •  Exploring & Extracting Insights from Data
  • Data Visualization Basics
  • Matplotlib – Hands-on
  • Seaborn – Hands-on
Statistical Thinking in Python (Part 1) Build the foundation
  • Thinking Statistically – Introduction
  • Measures of Central Tendency.
  • Measures of Dispersion.
  • IQR Statistics – Hands-On
Supervised Learning & Un-Supervised Learning
  •  1. Classification vs Regression.
  • Supervised vs Unsupervised Learning.
  • Linear Regression – Hands-on.
  • Metrics in Linear Regression – Hands-on.
  • Fine-Tuning Your Model
Logistic and Linear regression
  • Introduction to Logistic/Linear Regression.
  • Hands-on with Logistic/Linear Regression.
  • Metrics in Logistic/Linear Regression.
Pre-processing for Machine Learning in Python
  •  1. Introduction to Data Preprocessing.
  • Exploratory Data Analysis (EDA).
  • Missing Values.
  • Outliers
  • Standardizing Data / Scaling Techniques.
  • Feature Scaling and Feature Selection.
Tree Based Models Classification and Regression Tree
  • Decision Tree.
  • Boosting Random Forest.
  • Bagging
Fundamentals of Neural Networ
  • Neural Network
SQL
  • Basics of database schema.
  • Importance SQL Clauses
    SQL Joins
POWER BI
  •  Introduction to Power BI desktop.
  • ETL pipeline in Power BI.
  • Calculating fields with DAX.
  • Visualising data with reports.
  • AI functionalities of Power BI

Important Course Highlights

  • Pre – Recorded Content.
  • Live Group Q&A Session.
  • Course Community.
  • Unlimited Lifetime Access.
  • Internship Opprtunity.
  • Certificate Of Completion.
  • 00Hours
  • 00Minutes
  • 00Seconds
  • Date : 15 January, 2025
  • Time : Depends on the availability of student
  • Location : Online Classes

Course Description

Our Data Science course is designed for those starting their journey or seeking to advance their skills. Covering everything from foundational concepts to advanced techniques, this course ensures you’re ready for real-world challenges, no matter your background.Whether you’re a beginner or looking to level up your skills, this course provides everything you need to excel in the rapidly growing field of data science.

Course Content

  • Over 40+ lectures and 16+ hours of comprehensive Data Science content!
  • LIVE PROJECT: End-to-End Data Science Model Development Included.
  • Learn Data Science, Data Preprocessing, and Model Building from an industry expert—right from your own desk.
  • Information-packed practical training covering everything from fundamental DS concepts to advanced algorithms and techniques.
  • Ideal for beginners as well as advanced learners, especially those who grasp concepts faster through hands-on demonstrations.

Why Choose Us?

  • Industry Expertise : Learn from experienced instructors who know what it takes to succeed.
  • Skill Development : Pick a self-guided or mentor-led program that fits your learning style.
  • Community : Join a vibrant community where you can connect with peers, participate in events, and build lasting relationships
  • Career Support : Access job placement assistance and resources to help you land your dream job.
  • Different Levels of Programs : Live, Recorded and Professional Programs.

What You Will Learn By This Course

Data Visualization

Data Visualization

Data Analysis

Data Analysis

Building Models

Building Models

Certificates

Our Mentors

Our Programs

Self Paced

Rs. 7,499 Rs. 5,999
  • Ideal for independent learners.
  • 1 year access to recorded sessions.
  • Multi-channel doubt resolution support.
  • Learn from experienced instructors who know what it takes to succeed.
Choose Plan

Mentor Led

Rs. 11,250 Rs. 8,999
  • 24/7 support
  • Personalized guidance & networking.
  • Real-time doubt resolution with mentors.
  • Live classes (Post 6 PM) + lifetime access to recordings.
  • Learn from experienced instructors who know what it takes to succeed.
Choose Plan

Placement Assistance

Rs. 14,999 Rs. 11,999
  • Interview preparation( mock hr, communication, resume building)
  • Multi-channel doubt resolution support.
  • 100% interviews schedule
  • 100% job assistance
  • Learn from experienced instructors who know what it takes to succeed.
Choose Plan

How Can We Help You

What are the prerequisites for enrolling in the Data Science Course?

Basic programming knowledge in Python and a fundamental understanding of mathematics, particularly linear algebra and calculus, are recommended. No advanced prerequisites are required.

Who should take this Data Science course?

This course is ideal for beginners wanting to enter the field of machine learning, data enthusiasts looking to deepen their knowledge, career changers transitioning into data science, and professionals seeking to enhance their skills in machine learning.

What topics are covered in Data Science course?

Look at the top-left drop-downs to know all the topics covered.

How long is this course

The course typically spans 6-8 weeks, depending on your pace, including lectures, assignments, and hands-on projects.

Will I recieve a certificate on completion of this course?

Yes, you will receive a certificate of completion and a Letter of Recommendation upon successfully finishing the course and all required assignments and projects.