Introduction to Applied Data Science with Python

5.0

(10 ratings)

·

6 Weeks

·

Cohort-based Course

Gain essential data science skills with Python to address real-world challenges. Prepare for a future in data science in only 6 weeks.

Previously at

Freddie Mac
Citi
Guidehouse

Course overview

Describe the transformation students will have in your course

👩‍🏫 ABOUT THE INSTRUCTOR:


Dr. Sudip Shrestha is a seasoned data science leader with over 10 years of experience in applying AI and data science across various industries. His expertise spans from advanced analytics and machine learning to leading data science projects and teams. Dr. Shrestha's passion for teaching and sharing his insights in AI/ML makes him an exceptional mentor for those aspiring to enter or progress in the data science and AI fields.


👩‍💻 ABOUT THE COURSE

This 6-week course is designed to empower you with the essential skills in Python for data science. It's perfect for those with no prior experience in programming or data science, as well as for professionals looking to upskill.


You will start from the basics of Python programming, gradually moving into more complex areas such as data manipulation, analysis, visualization, and real-world application. By the end of the course, you will be comfortable in using Python for various data science tasks, enabling you to analyze and interpret complex datasets effectively.


🌟 WHY THIS COURSE STANDS OUT

⭐️ Tailored for absolute beginners, making complex concepts accessible and easy to understand.


⭐️ Focus on practical applications, ensuring skills learned are immediately applicable in real-world scenarios.


⭐️ Comprehensive coverage of essential data science tools and techniques within a short timeframe.


⭐️ A perfect blend of theory and hands-on practice, including a real-world project to showcase new skills.

Who is this course for

01

Aspiring Data Scientists: Beginner data analysts or data scientists looking to enhance their foundational skills in data science and Python.

02

Business Professionals: Business analysts, managers, or any professionals who aim to utilize data science for better decision-making.

03

Non-Coders Seeking a Career Change: Professionals from non-technical backgrounds who want to transition into the data science field.

What you’ll get out of this course

Understanding Data Science & Python Basics:

You will gain a foundational understanding of data science, its key concepts including AI and ML, and the role of Python in data science. You'll also learn to write simple Python scripts and understand basic programming concepts​​.

Data Analysis with Pandas and NumPy

You will learn techniques for data manipulation, cleaning, and preparation. This includes understanding the importance of data quality and how to perform data analysis using Python's powerful libraries, Pandas and NumPy​​.

Data Visualization with Python

You will understand the importance and principles of effective data visualizations and how they can drive business value. You'll gain hands-on experience in creating visualizations, customizing plots, and generating insights from visual data using Matplotlib and Seaborn libraries

Machine Learning Fundamentals

You will demystify the world of machine learning, learning about its lifecycle, various types (supervised, unsupervised, reinforcement learning), and key concepts necessary for developing machine learning models​​.

Practical Machine Learning Application

You will apply your learning to build and evaluate a basic machine learning model using the Scikit-Learn library. This includes understanding model selection, overfitting, and applying linear regression on a dataset​​.

How to use ChatGPT for Effective Learning

You will understand the capability of ChatGPT and how to effectively use it for simple data science queries. This includes best practices in prompt engineering and responsible use of AI.

Capstone Project

You will have the opportunity to apply all the skills learned throughout the course in a Capstone Project. This project will allow you to demonstrate your ability to analyze, visualize, and model data to predict outcomes, simulating real-world data science tasks

DISCOUNT

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This course includes

6 interactive live sessions

Lifetime access to course materials

36 in-depth lessons

Direct access to instructor

Projects to apply learnings

Guided feedback & reflection

Private community of peers

Course certificate upon completion

Maven Satisfaction Guarantee

This course is backed by Maven’s guarantee. You can receive a full refund within 14 days after the course ends, provided you meet the completion criteria in our refund policy.

Course syllabus

Expand all modules
  • Week 1

    May 25—May 26

    Week dates are set to instructor's time zone

    Events

    • May

      25

      Session 1

      Sat, May 25, 10:00 PM - 11:30 PM UTC

    Modules

    • Introduction to Data Science and Python Basics

  • Week 2

    May 27—Jun 2

    Week dates are set to instructor's time zone

    Events

    • Jun

      1

      Session 2

      Sat, Jun 1, 10:00 PM - 11:30 PM UTC

    Modules

    • Introduction to Data Analysis with Pandas and NumPy

    • Project 1 - Data Analysis

  • Week 3

    Jun 3—Jun 9

    Week dates are set to instructor's time zone

    Events

    • Jun

      8

      Session 3

      Sat, Jun 8, 10:00 PM - 11:30 PM UTC

    Modules

    • Data Visualization with Python

  • Week 4

    Jun 10—Jun 16

    Week dates are set to instructor's time zone

    Events

    • Jun

      15

      Session 4

      Sat, Jun 15, 10:00 PM - 11:30 PM UTC

    Modules

    • Introduction to Basic Statistics and Machine Learning

  • Week 5

    Jun 17—Jun 23

    Week dates are set to instructor's time zone

    Events

    • Jun

      22

      Session 5

      Sat, Jun 22, 10:00 PM - 11:30 PM UTC

    Modules

    • How to use ChatGPT as a Data Scientist

  • Week 6

    Jun 24—Jun 29

    Week dates are set to instructor's time zone

    Events

    • Jun

      29

      Session 6

      Sat, Jun 29, 10:00 PM - 11:30 PM UTC

    Modules

    • Capstone Project Presentation & Course Wrap-Up

  • Bonus

    Modules

    • Recordings of all Live Sessions via Maven

    • Data Science Notes and Cheat Sheets

    • Developers Guide

    • Interview Tips

    • Resume/CV Tips

5.0

(10 ratings)

What students are saying

Meet your instructor

Dr. Sudip Shrestha

Dr. Sudip Shrestha


Hey Everyone,

Excited to be here! I'm a Data Science and AI/ML Lead, passionate about modeling and analytics. I love teaching and sharing knowledge, which I do through creating courses and my YouTube channel, diving into all things data and AI. Looking forward to sharing insights and learning with this amazing community!

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Join an upcoming cohort

Introduction to Applied Data Science with Python

Cohort 2

$500 USD

Dates

May 25—June 29, 2024

Payment Deadline

June 28, 2024
|

Bulk purchases

Course schedule

4-6 hours per week
  • Saturdays

    5:00 PM- 6:30 PM EST

    We'll meet for our live session.

  • April 27, 2024

    Class begins.

  • Homework/Projects

    2-4 hours per week

    You'll spend about 2-4 hours per week for homework or project.


Learning is better with cohorts

Learning is better with cohorts

Active hands-on learning

This course builds on live workshops and hands-on projects

Interactive and project-based

You’ll be interacting with other learners through breakout rooms and project teams

Learn with a cohort of peers

Join a community of like-minded people who want to learn and grow alongside you

Frequently Asked Questions

What happens if I can’t make a live session?
I work full-time, what is the expected time commitment?
What’s the refund policy?
Does Sudip offer private cohorts for teams?
Why this course?
Can I reach out to instructor after the course is ended?
Is the course Live?
A pattern of wavy dots
Join an upcoming cohort

Introduction to Applied Data Science with Python

Cohort 2

$500 USD

Dates

May 25—June 29, 2024

Payment Deadline

June 28, 2024
|

Bulk purchases

$500 USD

5.0

(10)

·

6 Weeks