Course content
Introduction to Data Science
- What is Data Science?
- What is Machine Learning?
- What is Deep Learning?
- What is AI?
- Data Analytics & it’s types
Python Programming Fundamentals
- Programming Basics
- Python Data Types
- Structures and conditional statements
- Python core packages
- Introduction to Jupyter Notebook
Data Science Essentials
- Data Science Introduction
- Data Science work flow
- Machine Learning Overview
Data Mugging with Numpy and Pandas
- Introduction to Numpy and Pandas
- Data filtering and selecting
- Find duplicates and treating missing values
- Concatenate and transform data
Basic Statistics
Central Tendency
- Mean
- Median
- Mode
- Skewness
- Normal Distribution
Probability Basics
- What does it mean by probability?
- Types of Probability
- ODDS Ratio?
Standard Deviation
- Data deviation & distribution
- Variance
Bias variance Tradeoff
- Underfitting
- Overfitting
Distance metrics
- Euclidean Distance
- Manhattan Distance
Outlier analysis
- What is an Outlier?
- Inter Quartile Range
- Box & whisker plot
- Upper Whisker
- Lower Whisker
- catter plot
- Cook’s Distance
Missing Value treatments
- What is an NA?
- Central Imputation
- KNN imputation
- Dummification
Correlation
- Pearson correlation
- Positive & Negative correlation
Error Metrics Duration
- Classification
- Confusion Matrix
- Precision
- Recall
- Specificity
- F1 Score
Regression
- MSE
- RMSE
- MAPE
Visualization, web scraping
- Creating basic charts
- Statistical Charts
- Web Scrapping tools
Introduction to Machine Learning
- Overview of Supervised and Unsupervised Machine Learning
- Linear Regression
- Clustering with K-means
- Naive Bayes Classification
- Introduction to Neural Networks
Supervised Learning
- Linear Regression
- Linear Equation
- Slope
- Intercept
- R square value
- Logistic regression
- ODDS ratio
- Probability of success
- Probability of failure
- ROC curve
- Bias Variance Tradeoff
Unsupervised Learning
- K-Means
- K-Means ++
- Hierarchical Clustering
Other Machine Learning algorithms
- K – Nearest Neighbour
- Naïve Bayes Classifier
- Decision Tree – CART
- Decision Tree – C50
- Random Forest
To see the full course content Download now
Course Prerequisites
- Basic Programming is recommended
- Basic Statistics knowledge is recommended
Who can attend
- Candidates wanted to pursue Data Science career, with basic or no programming skills
- Seasoned conventional programmer aiming to gain basic machine learning coding skills
- Job seekers, pursuing a career as Data Science Developer
- Professionals, whose job involves Data Science and Python.
Number of Hours: 50hrs
Certification
Key features
- One to One Training
- Online Training
- Fastrack & Normal Track
- Resume Modification
- Mock Interviews
- Video Tutorials
- Materials
- Real Time Projects
- Virtual Live Experience
- Preparing for Certification
FAQs
DASVM Technologies offers 300+ IT training courses with 10+ years of Experienced Expert level Trainers.
- One to One Training
- Online Training
- Fastrack & Normal Track
- Resume Modification
- Mock Interviews
- Video Tutorials
- Materials
- Real Time Projects
- Materials
- Preparing for Certification
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Learn from experts active in their field, not out-of-touch trainers. Leading practitioners who bring current best practices and case studies to sessions that fit into your work schedule. We have a pool of experts and trainers are composed with highly skilled and experienced in supporting you in specific tasks and provide professional support. 24x7 Learning support from mentors and a community of like-minded peers to resolve any conceptual doubts. Our trainers has contributed in the growth of our clients as well as professionals.
All of our highly qualified trainers are industry experts with at least 10-12 years of relevant teaching experience. Each of them has gone through a rigorous selection process which includes profile screening, technical evaluation, and a training demo before they are certified to train for us. We also ensure that only those trainers with a high alumni rating continue to train for us.
No worries. DASVM technologies assure that no one misses single lectures topics. We will reschedule the classes as per your convenience within the stipulated course duration with all such possibilities. If required you can even attend that topic with any other batches.
DASVM Technologies provides many suitable modes of training to the students like:
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