Class is in session
5.0
(12 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.
Class is in session
5.0
(12 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
Course overview
👩🏫 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.
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.
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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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.
Introduction to Applied Data Science with Python
Week 1
Aug 12—Aug 18
Events
Mon, Aug 12, 10:00 PM - 11:30 PM UTC
Modules
Week 2
Aug 19—Aug 25
Events
Mon, Aug 19, 10:00 PM - 11:30 PM UTC
Modules
Week 3
Aug 26—Sep 1
Events
Mon, Aug 26, 10:00 PM - 11:30 PM UTC
Modules
Week 4
Sep 2—Sep 8
Events
Mon, Sep 2, 10:00 PM - 11:30 PM UTC
Modules
Week 5
Sep 9—Sep 15
Events
Mon, Sep 9, 10:00 PM - 11:30 PM UTC
Modules
Week 6
Sep 16
Events
Mon, Sep 16, 10:00 PM - 11:30 PM UTC
Modules
Bonus
Modules
5.0
(12 ratings)
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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4-6 hours per week
Mondays
6:00 PM - 7:30 PM EST
We'll meet for our live session.
Aug 12, 2024
Class begins.
Homework/Projects
2-4 hours per week
You'll spend about 2-4 hours per week for homework or project.
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
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?
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