Introduction to Python for Data Science
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Catogory
Data Science & Business Intelligence
Duration Time
45 hours
Price
Rs. 2000
Data science has become a great trend in computational and predictive statistical analysis. It’s also used by various organizations to make data-driven decisions. With all the challenges faced, Python has become an indispensable tool for the data science analyst and an important tool for any data scientist.
EduInPro’s Introduction to Python for Data Science course will help you master the techniques of data science and analytics using Python. With this Python for Data Science Course, you’ll also learn the essential concepts of Python programming and gain deep knowledge in data analytics, machine learning, data visualization, web scraping, and natural language processing. Python is a required skill for pursuing a career in Data Science industry.
The EduInPro approach on Introduction to Python for Data Science:
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Introduction to Data Science
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Python Essentials for Data Science
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Data Science ToolBox
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Importing & Cleaning Data
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Data Visualization with Statistical Thinking
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Introduction to Machine Learning with Scikit-Learn
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Practice with Case Studies
Introduction to Python for Data Science Modules
Objective
What is Data Science?
Data Science Tutorial – History
Data Science Tutorial – Methodologies
- Machine Learning for Pattern Discovery
- Machine Learning for Making Predictions
- Predictive Causal Analytics
- Prescriptive Analytics
Applications of Data Science
- Image Recognition
- Speech Recognition
- Internet Search
- Digital Advertisements
- Recommender Systems
- Price Comparison Websites
- Gaming
- Delivery Logistics
- Fraud and Risk Detection
Business Intelligence vs Data Science
Data Science Tutorial – Life-Cycle
- Discovery
- Data Preparation
- Model Planning
- Model Building
- Communicate results
- Operationalize
Why Python?
Python 2.x or 3.x- Which should you go for?
Data Science Tutorial – Python Libraries
Learning in Data Science Tutorial
Conclusion
Course Outline
- Objective
- What is Data Science?
- Data Science Tutorial – History
- Data Science Tutorial – Methodologies
- Machine Learning for Pattern Discovery
- Machine Learning for Making Predictions
- Predictive Causal Analytics
- Prescriptive Analytics
- Applications of Data Science
- Image Recognition
- Speech Recognition
- Internet Search
- Digital Advertisements
- Recommender Systems
- Price Comparison Websites
- Gaming
- Delivery Logistics
- Fraud and Risk Detection
- Business Intelligence vs Data Science
- Data Science Tutorial – Life-Cycle
- Discovery
- Data Preparation
- Model Planning
- Model Building
- Communicate results
- Operationalize
- Why Python?
- Python 2.x or 3.x- Which should you go for?
- Data Science Tutorial – Python Libraries
- Learning in Data Science Tutorial
- Conclusion
What do I need to do to unlock my Eduinpro certificate?
Online Classroom:
- Attend one complete batch
- Successful completion and evaluation of any one of the given projects
Online Self-learning:
- Complete 85% of the course
- Successful completion and evaluation of any one of the given projects
Featured Review
Anup Acharya
I Attended a 2 day weekend course by EduInPro for the Introduction to Python for Data Science certification. The instructor was very knowledgeable and engaging. Had Excellent learning and experience.
Bhibudatta
I attended training for Introduction to Python for Data Science and the training was very interactive and helpful. Got clarity on many concepts related to Scrum Master role.
Sreeram Narayan
I came across EduInPro for Introduction to Python for Data Science . The training was interesting and trainer made the class fun and interesting and the sessions very knowledgeable on the topic!
Namratha Kulkarni
Course with EduInpro was a well-organized one with an excellent tutor. The course included both theoretical and practical real-life cases and hands-on sessions which made training interesting.
Iqbal Arif
EduInPro’s Introduction to Python for Data Science was excellent and it got numerous concepts together in a simple, practical and detailed package. I highly recommend EduInPro’s PMP training even if you don't plan to sit for the PMP exam.
Ruthvik Sharma
I came across EduInPro’s Introduction to Python for Data Science online and its self-paced module encouraged me to take up the course and made me more proactive with my learning. I took detailed notes, and attended the classes to fit in with my busy schedule and was happy with the course.
Garima Khera
EduInPro’s Introduction to Python for Data Science training were so well designed. The hands-on projects helped me understand the theory sessions in depth and apply them on my website.
FREQUENTLY ASKED QUESTIONS
This Course is intended for Individuals wanting to understand a deeper level of data science using more advanced techniques and operations and individuals wanting to expand their knowledge of Python while learning data science; IT specialists aspiring to learn a new skill set; statisticians; computer scientists; and IT analysts etc.
Earning EduInPro Data Science with Python Certification can help candidate differentiate in today's competitive job market, broaden their employment opportunities by displaying their advanced skills, and result in higher earning potential.
IT specialists aspiring to learn a new skill set; statisticians; computer scientists; and IT analysts etc.
Data science is a way to try and discover hidden patterns in raw data. To achieve this goal, it makes use of several algorithms, machine learning (ML) principles, and scientific methods. The insights it retrieves from data lie in forms structured and unstructured. So in a way, this is like data mining. Data science encompasses all- data analysis, statistics, and machine learning. With more practices being labeled into data science, the term itself becomes diluted beyond usefulness. This leads to variation in curricula for introductory data science courses worldwide.
Python the best choice for it? Here are a few reasons-
• Open-source and free.
• Easy to learn; intuitive.
• Fewer lines of code.
• Portability.
• Better productivity.
• Demand and popularity.
• Excellent online presence/ community.
• Support for many packages usable with analytics projects; can also use packages that can use code from other languages.
• It is faster than similar tools like R and MATLAB.
• Amazing memory management abilities.
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