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Natural Language Processing Real-World Projects in Python
Solve 3 real Business Problems. Build Robust AI, NLP models for Sentiment, Security and Stock News Domain..


Requirements

Basic knowledge of programming is recommended. However, You can follow my Basics of Python Course which is free of cost therefore, the course has no prerequisites, and is open to anyone with basic programming knowledge. Students who enroll in this course will master data science and directly apply these skills to solve real world challenging business problems.

Description

Are you looking to land a top-paying job in Data Science , AI and Natural Language Processing?

Or are you a seasoned AI practitioner who want to take your career to the next level?

Or are you an aspiring data scientist who wants to get Hands-on Data Science and Artificial Intelligence?


If the answer is yes to any of these questions, then this course is for you!

Data Science is one of the hottest tech fields to be in right now! The field is exploding with opportunities and career prospects. Data Science is widely adopted in many sectors nowadays such as banking, healthcare, Airlines, Logistic and technology.

In business, Data Science is applied to optimize business processes, maximize revenue and reduce cost. The purpose of this course is to provide you with knowledge of key aspects of data science applications in business in a practical, easy and fun way. The course provides students with practical hands-on experience using real-world datasets.


1.Task #1 @Predict Customer Sentiments : Develop an AI model to predict Customer Sentiments of Amazon..

3.Task #2 @Predict future Stock Prices: Develop NLP models to predict future Stock prices.

2.Task #3 @Predict the strength of a Password: Predict the category of Password whether it is Strong, Good or Weak.

Why should you take this Course?

It explains Projects on real Data and real-world Problems. No toy data! This is the simplest and best way to become a Data Scientist/AI Engineer/ ML Engineer/NLP Engineer

It shows and explains the full real-world Data. Starting with importing messy data, cleaning data, merging and concatenating data, grouping and aggregating data, Exploratory Data Analysis through to preparing and processing data for Statistics, Machine Learning , NLP and Time Series and Data Presentation.


In real-world projects, coding and the business side of things are equally important. This is probably the only course that teaches both: in-depth Python Coding and Big-Picture Thinking like How you can come up with a conclusion

Guaranteed Satisfaction: Otherwise, get your money back with 30-Days-Money-Back-Guarantee.


Who this course is for:

One who is curious about to do Carrier Transition into Data Science, AI , Natural Language Processing,

Course content
4 sections • 36 lectures • 5h 17m total length

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