Data Science & ML for Python-Python & Data Science Made Easy
What you'll learn
- Python & R programming for Structured data/ tables.
- Python in demand packages used by Data Scientist and Machine Learning professionals.
- Basic, Inferential and Advanced Statistics
- Concept of Linear and Logistic Regression implementing with Python code
- Machine Learning (ML) Algorithms concepts with Python code
- ML Algorithms - Support Vector Machine
- Machine Learning Algorithms. - K nearest neighbors
- Practical Application of Data Science and Machine Learning in Healthcare and Real estate Industry
- An approach and outlook a Data Scientist and ML professional should adopt while solving business problems in real life
- Engaging Course with Multiple choice questions for Students towards end of each section for Knowledge tests
- Practical & Comprehensive Assignment with Guidelines explaining challenges faced by DS/ML professional and how to deal with such roadblocks.
- No pre-requisites. Good to have knowledge of Statistics and/or Programming
This course is for Aspirant Data Scientists, Business/Data Analyst, Machine Learning & AI professionals planning to ignite their career/ enhance Knowledge in niche technologies like Python and R. You will learn with this program:
✓ Basics of Python, marketability and importance
✓ Understanding most of python programming from scratch to handle structured data inclusive of concepts like OOP, Creating python objects like list, tuple, set, dictionary etc; Creating numpy arrays, ,Creating tables/ data frames, wrangling data, creating new columns etc.
✓ Various In demand Python packages are covered like sklearn, sklearn.linear_model etc.; NumPy, pandas, scipy etc.
✓ R packages are discussed to name few of them are dplyr, MASS etc.
✓ Basics of Statistics - Understanding of Measures of Central Tendency, Quartiles, standard deviation, variance etc.
✓ Types of variables
✓ Advanced/ Inferential Statistics - Concept of probability with frequency distribution from scratch, concepts like Normal distribution, Population and sample
✓ Statistical Algorithms to predict price of houses with Linear Regression
✓ Statistical Algorithms to predict patient suffering from Malignant or Benign Cancer with Logistic Regression
✓ Machine learning algorithms like SVM, KNN
✓ Implementation of Machine learning (SVM, KNN) and Statistical Algorithms (Linear/ Logistic Regression) with Python programming code
Who this course is for:
- Machine Learning
- Data Science
- R programming
Steven is a Data Scientist and ML Professional. He has extensive industry experience into large variety of technologies. He is passionate about delivering excellence in trainings with great visualizations.
Ø He is an Engineer Computer Science. BI and ETL Developer with 15 years of experience. Had worked into various ETL and Analytics tools platforms like Python, Alteryx, Tableau, SAS Data Integration Studio, Informatica, Hadoop and Spark big data platforms.
Ø Training Experience: Had been training since last 8 years into experience technologies. Passionate about training.
Ø Has extensive experience in industry domains like Telecom, Manufacturing, Banking and Health Insurance.
Ø Delivered projects around:
1. SDLC of a Manufacturing domain with Alteryx and SAS DI Studio
2. Alteryx Process Application for a telecom company
3. Tableau reports for a health insurance company
4. Data Analytics solutions with SAS & Python predictive and forecasting tools.