ATOM is a leading training institute that provides training programs in Coimbatore and
therefore has been successfully providing the best environment for learning Data Science with Python training in Tamil Nadu. Since, Atom provides up-to-date syllabus, reliable course materials, highly proficient trainers and an advanced computer lab infrastructure it is considered to be the one of the best institutes in South India. Moreover, we have the best-ever placement care as the result of the developed training programs we create. Few of the features of our training are given below:
- Comprehensive advanced concepts are used in formulation of this syllabus, primarily, based on current industry requirements by field experts.
- Our ultimate goal in creating this syllabus is to produce future experts and thus, equip the industry with the man power it requires.
- All the recent developments in this segments are taken in account to create such a comprehensive syllabus.
- Our curriculum Includes writing real time programs in Python and performing real-time tasks to analyze Data science concepts with various test case scenarios.
- Experts with immense experience in the subject matter handle classes.
- Our resources have in-depth understanding of the concepts and the technologies.
- Our tutors possess good communication and soft skills.
- Our tutors also provide emotional and technical support when required.
- We undertake special doubt clarification sessions every week in order to, help our students practice better and understand better.
- We have an advanced computer lab with updated version of Python and many data science tools as per requirement.
- We provide student friendly classrooms with digital board to explain concepts.
- Periodical Video Conferencing with the industry experts in various topics, case classes and trouble shooting sessions keeps our students in tempo with what’s happening in the industry.
- Our facilities are Wifi enabled at all times hence, helping the students stay connected at all times.
- We provide 100 % placement assistance to all the students enrolled in this program.
- Highly skilled placement team works round the clock therefore, it facilitate setting up job interviews with leading corporates in this field.
- Our program includes free classes on communication skills, resume preparation and cover letter.
- We conduct mock interviews and sample tests in data science field ultimately, to prepare candidates before the interview.
Data Science with Python Course Syllabus
Lesson 1: Data Science Overview
- Data Science
- Data Scientists
- Examples of Data Science
- Python for Data Science
Lesson 2: Data Analytics Overview
- Introduction to Data Visualization
- Processes in Data Science
- Data Wrangling, Data Exploration, and Model Selection
- Exploratory Data Analysis or EDA
- Data Visualization
- Hypothesis Building and Testing
Lesson 3: Statistical Analysis and Business Applications
- Introduction to Statistics
- Statistical and Non-Statistical Analysis
- Some Common Terms Used in Statistics
- Data Distribution: Central Tendency, Percentiles, Dispersion
- Bell Curve
- Hypothesis Testing
- Chi-Square Test
- Correlation Matrix
- Inferential Statistics
Lesson 4: Python: Environment Setup and Essentials
- Introduction to Anaconda
- Installation of Anaconda Python Distribution – For Windows, Mac OS, and Linux
- Jupyter Notebook Installation
- Jupyter Notebook Introduction
- Variable Assignment
- Basic Data Types: Integer, Float, String, None, and Boolean; Typecasting
- Creating, accessing, and slicing tuples
- Creating, accessing, and slicing lists
- Creating, viewing, accessing, and modifying dicts
- Creating and using operations on sets
- Basic Operators: ‘in’, ‘+’, ‘*’
- Control Flow
Lesson 5: Mathematical Computing with Python (NumPy)
- NumPy Overview
- Properties, Purpose, and Types of ndarray
- Class and Attributes of ndarray Object
- Basic Operations: Concept and Examples
- Accessing Array Elements: Indexing, Slicing, Iteration, Indexing with Boolean Arrays
- Copy and Views
- Universal Functions (ufunc)
- Linear Algebra
Lesson 6: Scientific computing with Python (Scipy)
- SciPy and its Characteristics
- SciPy sub-packages
- SciPy sub-packages –Integration
- SciPy sub-packages – Optimize
- Linear Algebra
- SciPy sub-packages – Statistics
- SciPy sub-packages – Weave
- SciPy sub-packages – I O
Lesson 7: Data Manipulation with Python (Pandas)
- Introduction to Pandas
- Data Structures
- Missing Values
- Data Operations
- Data Standardization
- Pandas File Read and Write Support
- SQL Operation
Lesson 8: Machine Learning with Python (Scikit–Learn)
- Introduction to Machine Learning
- Machine Learning Approach
- How Supervised and Unsupervised Learning Models Work
- Supervised Learning Models – Linear Regression
- Supervised Learning Models: Logistic Regression
- K Nearest Neighbors (K-NN) Model
- Unsupervised Learning Models: Clustering
- Unsupervised Learning Models: Dimensionality Reduction
- Model Persistence
- Model Evaluation – Metric Functions
Lesson 9: Natural Language Processing with Scikit-Learn
- NLP Overview
- NLP Approach for Text Data
- NLP Environment Setup
- NLP Sentence analysis
- NLP Applications
- Major NLP Libraries
- Scikit-Learn Approach
- Scikit – Learn Approach Built – in Modules
- Scikit – Learn Approach Feature Extraction
- Bag of Words
- Extraction Considerations
- Scikit – Learn Approach Model Training
- Scikit – Learn Grid Search and Multiple Parameters
Lesson 10: Data Visualization in Python using Matplotli
- Introduction to Data Visualization
- Python Libraries
- Matplotlib Features:
- Line Properties Plot with (x, y)
- Controlling Line Patterns and Colors
- Set Axis, Labels, and Legend Properties
- Alpha and Annotation
- Multiple Plots
- Types of Plots and Seaborn
Lesson 11: Data Science with Python Web Scraping
- Web Scraping
- Common Data/Page Formats on The Web
- The Parser
- Importance of Objects
- Understanding the Tree
- Searching the Tree
- Navigating options
- Modifying the Tree
- Parsing Only Part of the Document
- Printing and Formatting
Lesson 12: Python integration with Hadoop, MapReduce and Spark
- Need for Integrating Python with Hadoop
- Big Data Hadoop Architecture
- ClouderaQuickStart VM Set Up
- Apache Spark
- Resilient Distributed Systems (RDD)
- Spark Tools
- PySpark Integration with Jupyter Notebook
There are no official certification for Data Science with Python training. However, Atom provides its own certification program. On successful completion of the course the candidates will receive course completion certificates.
When you are studying at the best institute in Coimbatore, you don’t have to worry about certification to get a job or propel your career. Our training program will help you develop
your own skill sets in both Data Science and Python training, therefore our placement program will ensure that all our candidates get good placement opportunities after completing our course.
On completing our Data Science with Python training at Atom, our candidates will have many job openings in companies all over the world. Some of the job designations you can apply, are listed below:
- Python Developer – Machine Learning/Data Science
- Business Analyst with Python
- Data Scientist with Python
- Data Analyst