Data Science Training

Breadcrumb Abstract Shape
Breadcrumb Abstract Shape
Breadcrumb Abstract Shape

This course provides a complete introduction to the world of Data Science, guiding learners from foundational concepts to practical data analysis and visualization. You’ll gain hands-on experience in Python programming, data manipulation, SQL querying, and statistical analysis — empowering you to make sense of complex datasets and communicate insights effectively.

What Will You Learn?
  • Master Python for Data Analysis using libraries such as Pandas and NumPy.
  • Write and execute SQL queries to extract and manage data from relational databases.
  • Visualize and tell stories with data using tools like Matplotlib and Seaborn.
  • Apply core statistical and probabilistic concepts to analyze trends and patterns.
  • Clean, process, and transform raw data into actionable insights through hands-on exercises.
  • Complete a capstone project demonstrating your full data analysis workflow.

Material Includes

  • 20–25 hours of high-definition video lessons
  • Downloadable code files and practice datasets
  • Hands-on assignments and a final data analysis project
  • Access to an interactive student community forum
  • A verifiable Certificate of Completion from Skillsflick

Requirements

  • No prior data science experience is required.
  • Basic familiarity with programming concepts is helpful but not mandatory.
  • You’ll need a computer with internet access and the curiosity to explore data!

Audience

  • Aspiring Data Analysts and Data Scientists seeking a strong foundation.
  • Engineers and developers transitioning into data-centric roles.
  • Students and professionals from any background curious about how data drives modern decision-making.

Course Content

Module 1: Introduction to Python

  • Python Basic 1
    20:51
  • Python Basic 2
    05:59
  • Python Basic 3
    19:26
  • Python Basic 4
    00:00

Module 2: Object Oriented Programming(OOPs)
Object-Oriented Programming (OOP) is a programming paradigm based on the concept of objects, which combine data and behavior into a single unit. It focuses on four main principles — Encapsulation, Abstraction, Inheritance, and Polymorphism — to make code more modular, reusable, and easier to maintain. OOP helps model real-world entities, improving code structure and flexibility.

Module 3: Numpy

Module 4: Pandas
Pandas is a powerful Python library used for data analysis and manipulation. It provides easy-to-use data structures like Series (1D) and DataFrame (2D) for handling structured data efficiently. Key features include: Data Handling: Import and export data from formats like CSV, Excel, SQL, and JSON. Data Cleaning: Handle missing data, duplicates, and perform filtering or transformation. Data Analysis: Perform operations like grouping, aggregation, sorting, and merging. Data Visualization: Integrates easily with libraries like Matplotlib for visual analysis. In short, Pandas simplifies working with large datasets, making data cleaning, analysis, and visualization faster and more intuitive.

Module 5: Data Visualization

Module 6: Statistics

Tags

A course by

SKILLsFLICK

Student Ratings & Reviews

5.0
Total 3 Ratings
5
3 Ratings
4
0 Rating
3
0 Rating
2
0 Rating
1
0 Rating
SS
Shashank Sharma
7 months ago
Totally worth it !!
G
goohf
8 months ago
Thank you SKILLsFLick
GS
Govind singh
8 months ago
It was the best Experience

Course Includes:

  • Price:
    ₹5,000.00
  • Instructor:SKILLsFLICK
  • Duration: 25 hours
  • Lessons:15
  • Students:13
  • Level:All Levels
₹5,000.00

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