Hands on Real-World Projects on Various Domains of Data Science in Machine Learning, Natural Language Processing , Time Series Analysis
Develop Natural Language Processing Models to Customer Sentiments
Develop time series forecasting models to predict Prices of stocks
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.
Are you looking to land a top-paying job in Data Science?
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.
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 Price of Airlines Industry : Develop an AI model to predict Fare of Airlines at various Routes.
2.Task #2 @Predict the strength of a Password: Predict the category of Password whether it is Strong, Good or Weak.
3.Task #3 @Predict Prices of a Stock: Develop time series forecasting models to predict future Stock prices.
Why should you take this Course?
It explains Projects on real Data and real-world Problems. No toy data! This is the simplest & best way to become a Data Scientist/AI Engineer/ ML 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 & Time Series and Data Presentation.
It gives you plenty of opportunities to practice and code on your own. Learning by doing.
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 Thinkinglike 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 Data Science, AI, Machine Learning, Natural Language Processing, Time Series Analysis..
4 sections • 50 lectures • 7h 45m total length
Datasets & Resources
Extract Derived Features from Data
Perform Data Pre-processing
Handle Categorical Data & Feature Encoding
Perform Label Encoding on data
How to handle Outliers in Data
Select best Features using Feature Selection Technique
Applying Random Forest on Data & Automate predictions
Intuition Behind Decision Tree- Part 2
Intuition Behind Decision Tree- Part 3
Intuition Behind Decision Tree- Part 4
Intuition Behind Decision Tree- Part 5
Intuition Behind Decision Tree- Part 6
Intuition Behind Linear Regression- Part 1
Intuition Behind Linear Regression- Part 2
Intuition Behind Linear Regression- Part 3
Intuition Behind KNN- Part 1
Intuition Behind KNN- Part 2
Intuition Behind KNN- Part 3
Intuition Behind KNN- Part 4
Play with multiple Algorithms & dumping your model
Professionally, I am a Data Scientist having experience of 6 years in finance, retail and transport.From my courses you will straight away notice how I combine my own experience to deliver content in a easiest fashion. To sum up, I am absolutely passionate about Data Analytics and I am looking forward to sharing my own knowledge with you!