Data Science with Python
The Data Science with Python course provides hands-on training in using Python for data analysis, visualization, and machine learning. Participants learn to work with key libraries such as Pandas, NumPy, Matplotlib, and Scikit-learn to handle data, perform statistical analysis, and build predictive models. The course covers essential topics like data cleaning, exploratory data analysis, and model evaluation, equipping individuals with practical skills to extract insights and make data-driven decisions using Python
Training Calender
| Start Date | End Date | Start-End Time | Batch Type | Training Mode | Batch Status | Start Learning |
|---|---|---|---|---|---|---|
| 27th Sep 2024 | 25th Nov 2024 | 09:00 - 13:00 IST | Weekend | Online | (Open) | Enroll Now |
Course Syllabus
Module - 1 (Data Science Project Lifecycle)
Introduction to Types of Analytics
Project life cycle
An introduction to our E-learning platform
Module - 2 (Introduction To Basic Statistics Using R And Python)
RISKS & POLICIES
Data Types
Measure Of central tendency
Measures of Dispersion
Graphical Techniques
Skewness & Kurtosis
Box Plot
R
R Studio
Descriptive Stats in R
Python (Installation and basic commands) and Libraries
Jupyter notebook
Set up GitHub
Descriptive Stats in Python
Pandas and Matplotlib / Seaborn
Module - 3 (Probability And Hypothesis Testing)
Random Variable
Probability
Probability Distribution
Normal Distribution
SND
Expected Value
Sampling Funnel
Sampling Variation
CLT
Confidence interval
Assignments Session-1 (1 hr)
Introduction to Hypothesis Testing
Hypothesis Testing with examples
2 proportion test
2 sample t-test
Anova and Chisquare case studies
Module - 4 (Exploratory Data Analysis )
Visualization
Data Cleaning
Imputation Techniques
Scatter Plot
Correlation analysis
Transformations
Normalization and Standardization
Module - 5 (Linear Regression)
Principles of Regression
Introduction to Simple Linear Regression
Multiple Linear Regression
Module - 6 (Logistic Regression)
Multiple Logistic Regression
Confusion matrix
1.False Positive, False Negative
2.True Positive, True Negative
3.Sensitivity, Recall, Specificity, F1 score
Module - 7 ( Deployment)
R shiny
Streamlit
Module - 8 (Data Mining Unsupervised Clustering)
Supervised vs Unsupervised learning
Data Mining Process
Hierarchical Clustering / Agglomerative Clustering
Measure of distance
Types of Linkages
Visualization of clustering algorithm using Dendrogram
Non-Hierarchial
Measurement metrics of clustering – Within Sum of Squares,
Between Sum of Squares, Total Sum of Squares
Choosing the ideal K value using Scree plot / Elbow Curve
A general intuition for DBSCAN
Different parameters in DBSCAN
Metrics used to evaluate the performance of a model
Pro’s and Con’s of DBSCAN
1. Numeric – Euclidean, Manhattan, Mahalanobis
2. Categorical – Binary Euclidean, Simple
Matching Coefficient, jacquard’s Coefficient
3. Mixed – Gower’s General Dissimilarity Coefficient
1. Single Linkage / Nearest Neighbour
2. Complete Linkage / Farthest Neighbour
3. Average Linkage
4. Centroid Linkage
DBSCAN
Topics
A general intuition for DBSCAN
Different parameters in DBSCAN
Metrics used to evaluate the performance of a model
Pro’s and Con’s of DBSCAN
Module - 9 (Dimension Reduction Techniques)
Topics
PCA and tSNE
Why dimension reduction
Advantages of PCA
Calculation of PCA weights
2D Visualization using Principal components
Basics of Matrix algebra
Module - 10 ( Association Rules)
Topics
What is Market Basket / Affinity Analysis
Measure of association
Support
Confidence
Lift Ratio
Apriori Algorithm
Module - 11 ( Recommender System)
User-based collaborative filtering
Measure of distance/similarity between users
Driver for recommendation
Computation reduction techniques
Search-based methods / Item to-item collaborative filtering
Vulnerability of recommender systems
Our Reviews
What Says Our Happy Clients
CyberHunt IT Solutions stands out as a premier institution for anyone aspiring to build a career in cybersecurity. From their comprehensive curriculum to hands-on training, they offer an unparalleled learning experience that equips students with both theoretical knowledge and practical skills.
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Highly recommended.
One of the bestest institute to start your career in cyber security domain. I had a great learning experience here all thanks to Bhosle sir and team for all the support. His teaching Skills and efforts for placement of students are commendable. I highly recommend this institute to achive your goals.
Very Highly Hands on Experince on Cyber Security By Mr. Datta. and also have onsite Hands on Experince.
Very good enveroment and good staff and Highly recommended if any one is looking career in Cyber Security.
I had a great time doing Cyber Security course here and made me a great experience. They take a good care of students and regarding placements too. This institution helps the students to get a good opportunity to explore more.
I had the best experience here. I had completed cyber security training here. They take a good care of students and regarding placements too. They keep evolving themselves to the new infrastructure. The credit system that this institute follows is very unique and students get a good opportunity to explore more.
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Email Information
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Business : sales@cyberhuntit.com
Recruitment information / General – hr@cyberhuntit.com
Address
Meridian Plaza, office No-301A, 3rd floor, Ameerpet Rd, Greenlands, Begumpet, Hyderabad, Telangana 500016