Acent India is providing the Best Data Science Certification course in Gurgaon. Data science is a field of Computer Science that deals with handling data, developing algorithms for data analysis, preparing data for analysis, exploring the data, analyzing, and visualizing the data by combining multidisciplinary programming skills like PYTHON Programming, and computational mathematics and statistics to extract meaningful outcomes. Acent India Technoart is the best Data Science certification course institute in Gurgaon. We offer hands-on practical knowledge from basic to advanced level IT, Business & Multimedia courses. ” Data Science with Python “
Data Science is the most high-in-demand profession with humongous amounts of opportunities in this modern tech era. Data is the power and wheel to drive any organization. A Data Science certification today can get you straight to the peak of your career in your dream company.
At the Acent India Pvt Ltd training and course content have been designed as per the latest industry trends, and the training program is led by industry expert trainers having experience of more than 8 to 10 years in IT and Software fields. And have real-time project management experience.
Data Science with Python Course Syllabus Acent India Gurgaon
Introduction to Data Science with Python
- Introduction to Data Science
- What is Data?
- Scope of Python for Data Science
- Introduction to Python Pandas
- Python Numpy
- Python Matplotlib
- Python Scikit-learn
Python Basics
- Taking User input in Python
- Output using print() function
- Learn about Variables, expression conditions, and functions in Python
- Operators in python
- Python Data Types
- Strings
- List
- Tuples
- Sets
- Dictionary
- Arrays
- Looping Statements
- Flow Control Statements in Python (continue, break and pass)
- Using the Yield instead of Return
- Object-Oriented Programming in Python
- Inheritance
- Polymorphism
- Exception handling
Python Data Processing
- Understanding Data Processing with Python
- Performing Operations on Numpy Arrays
- Overview of Data Cleaning
- Slicing, Indexing, Manipulating Data Sets and Cleaning Pandas Dataframe
- Working with Missing Data in Pandas
- Python Pandas and CSV
- Reading CSV file format with Python
- Export Pandas dataframe to a CSV file
- Python Pandas and JSON
- Pandas | Parsing JSON Dataset
- Exporting Pandas DataFrame to JSON File
- Working with excel files using Pandas
- Python Relational Database
- Connect MySQL database using MySQL-Connector Python
- Python: MySQL Create Table
- Python MySQL – Insert into Table
- Python MySQL – Select Query
- Python MySQL – Update Query
- Python MySQL – Delete Query
- Database with Python NoSQL Database
- Python Datetime
- Data Wrangling in Python
- Pandas Groupby: Summarising, Aggregating, and Grouping data
- What is Unstructured Data?
- Label Encoding of datasets
- One Hot Encoding of datasets
Data Visualization with Python
- Data Visualization using Matplotlib
- Style Plots using Matplotlib
- Line chart in Matplotlib
- Bar Plot in Matplotlib
- Box Plot in Python using Matplotlib
- Scatter Plot in Matplotlib
- Heatmap in Matplotlib
- Three-dimensional Plotting using Matplotlib
- Time Series Plot or Line plot with Pandas
- Python Geospatial Data
- Other Plotting Libraries in Python
- Data Visualization with Python Seaborn
- Using Plotly for Interactive Data Visualization in Python
- Interactive Data Visualization with Bokeh
Statistics
- Measures of Central Tendency
- Statistics with Python
- Measuring Variance
- Normal Distribution
- Binomial Distribution
- Poisson Discrete Distribution
- Bernoulli Distribution
- P-value
- Exploring Correlation in Python
- Create a correlation Matrix using Python
- Pearson’s Chi-Square Test
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