Rapid technological advances in Data Science have been reshaping global businesses and putting performances on overdrive. As yet, companies are able to capture only a fraction of the potential locked in data, and data scientists who are able to reimagine business models by working with Python are in great demand.
Python is one of the most popular programming languages for high-level data processing, due to its simple syntax, easy readability, and easy comprehension. Python’s learning curve is low, and due to its many data structures, classes, nested functions and iterators, besides the extensive libraries, this language is the first choice of data scientists for analyzing, extracting information and making informed business decisions through big data.
This Data Science for Python programming course is an umbrella course covering major Data Science concepts like exploratory data analysis, statistics fundamentals, hypothesis testing, regression classification modeling techniques and machine learning algorithms.
Extensive hands-on labs and interview prep will help you land lucrative jobs.
Learn to analyze data with Python in this Data Science with Python comprehensive course.
- 42 hours of Instructor-led Training
- Interactive Statistical Learning with advanced Excel
- Comprehensive Hands-on with Python
- Covers Advanced Statistics and Predictive Modeling
- Learn Supervised and Unsupervised Machine Learning Algorithms
What You Will Learn
1. Tools & Technologies
Get acquainted with various analysis and visualization tools such as Matplotlib and Seaborn
2. Statistics for Data Science
Understand the behavior of data; build significant models using concepts of Statistics Fundamentals
3. Python for Data Science
Learn the various Python libraries to manipulate data, like Numpy, Pandas, Scikit-Learn, Statsmodel
4. Exploratory Data Analysis
Use Python libraries and work on data manipulation, data preparation and data explorations
5. Data Visualization using Python
Use of Python graphics libraries like Matplotlib, Seaborn etc.
6. Advanced Statistics & Predictive Modeling
ANOVA, Linear Regression using OLS, Logistic Regression using MLE, KNN, Decision Trees
Please note:
Live Online Classroom training
Apr 18 - May 23, 08:00 AM - 12:00 PM ( IST ) schedules (Weekend batch) 11 days
- Sat - Apr 18
- Sun - Apr 19
- Sat - Apr 25
- Sun - Apr 26
- Sat - May 02
- Sun - May 03
- Sat - May 09
- Sun - May 10
- Sat - May 16
- Sun - May 17
- Sat - May 23
Course Content
1 Intro to Data Science
2 Mastering Python
3 Probability & Statistics
4 Advanced Statistics & Predictive Modeling - I
5 Advanced Statistics & Predictive Modeling - II
6 Time Series Forecasting
7 Capstone Project
Who Should Attend
- Those Interested in the field of data science
- Those looking for a more robust, structured Python learning program
- Those wanting to use Python for effective analysis of large datasets
- Software or Data Engineers interested in quantitative analysis with Python
- Data Analysts, Economists or Researchers
