Data science, also known as data-driven science, is an interdisciplinary field about scientific methods, processes, and systems to extract knowledge or insights from data in various forms, either structured or unstructured, similar to data mining
Why this course ?
1.Data Scientist is one of the fastest-growing and highest paid jobs in tech.
2.Employers are waking up to the fact that employees with the ability to use data and analytics to solve business problems are increasingly valuable, whatever their background or position in an organization.
Scheduled Batches
Weekends (8 Weekends)
Weekend Class Room | 8.00 AM - 11.00 AM
Weekends (8 Weekends)
Weekend Online | 8.00 AM - 11.00 AM
Course Curriculum
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Data Science Course Content
1. Introduction about Data Science:
- What is data science?
- Need of data science?
- Use cases of Data science
- How is data science different from business intelligence?
- Who are data scientists?
2. Statistics:
Section 1: Descriptive Statistics
- Intro to Research Methods
- Central tendency & Variability and Central limit theorem
- Variance and Range parameters
- Normal & Sampling distributions
Section 2: Inferential Statistics
- Intro to Predictive modeling
- Hypothesis testing: t-tests/z-test(1-sample,paired sample)
- Correlation
- Regression
- Chi-square test
- Analysis of Variance (ANOVA)
Section 3: practice lab
3. R & Python Programming:
Section 1: Environment setup & R/Python language basics:
- Application of machine learning
- Understand Business Analytics and R, Python
- Knowledge on the R & python language
- Community and ecosystem
- Understand the use of 'R & python' in the industry
- Compare R, Python with other software in analytics
- Install R, Python and the packages useful for the course
- Perform basic operations in R, Python using command line
- Learn the use of IDE R, Python and Various GUI
Section 2: Exploratory Data Analysis (EDA) and Data Preprocessing techniques in R/Python language:
- Data structures & data types(Vectors, Matrices, Lists, Factors & Data frames/Pandas)
- Importing Data(from different
- File formats, Databases, Stats software and web)
- Exporting Data
- Viewing Data
- Handling Missing Values
- Date & Time
- Understanding the cor() in R & Python
- EDA functions like summarize(), list()
- Multiple packages in R & Python for data analysis
- The Fancy plots like Segment plot
- HC plot in R & Python
- Understanding on Data Visualization
- Graphical functions present in R & Python
- Plot various graphs like table plot, histogram, boxplot
- Customizing Graphical Parameters to improvise the plots
- How to use ggplot2/matplot libraries
Section 3: practice lab
4. Machine Learning:
Section 1: Classification
- Logistic Regression
- K-Nearest Neighbors (K-NN)
- Support Vector Machine (SVM)
- Naive Bayes
- Decision Tree Classification
- Random Forest Classification
- XG Boost Classification
- Evaluating Classification Models Performance like Confusion matrix, ROC curve, F-Score…
Section 2: Regression
- Simple Linear Regression
- Multiple Linear Regression
- Polynomial Regression
- Support Vector Regression (SVR)
- Decision Tree Regression
- Random Forest Regression
- Evaluating Regression Models Performance like R-Squared and Adjusted R-Squared Intuitions
Section 3: Clustering
- What is Clustering
- K- Means Clustering
- Hierarchical Clustering
- LDA (Latent Dirichlet allocation)
Section 4: Recommendation
- What is Recommendation
- Association rules using generator
- Content and Collaborative filtering recommendation techniques
- Recommendation engine building using R/Python libraries
5. Real Time Projects:
Section 1: Real time Projects
We will teach 2 Real time end to end projects in Health Care and Retail domain industries.
Section 2: Tableau
- Introduction about Tableau and building First Bar chart
- Time series, Aggregation, and Filters
- Maps, Scatterplots, and Dashboards
- Joining and Blending Data, PLUS: Dual Axis Charts
Section 3: Resume Preparation
Projects
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Data Science Project
We will provide 2 Real time projects.
FAQ's
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Can I attend a demo session before enrolment?
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What if I miss a class ?
If you miss a class we can provide recording video for particular session and same session you have to attend another batch also
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Will I get placement Assistance ?
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Do I receive a certificate for training ?
- Once you are successfully through the course you will be awarded with Covalent's Training certificate.
- Covalent certification has industry recognition and we are the preferred training partner for many MNCs.
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what support is available after the training?
Doubts clarification up to getting a job
Resume preparation
Malk interviews
Placement Assistance
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What Features do you provide?
- Led sessions with corporate trainers
- Course Material
- Real time projects with industry experts
- Day wise Assignments (Tasks)
- Lab facilities
- Placement assistance
- Resume preparation
- Software installation
- Doubts clarifications
Certifications
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Course Completion Certificate
- Once you are successfully through the course you will be awarded with Covalent's Training certificate.
- Covalent certification has industry recognition and we are the preferred training partner for many MNCs.
Videos
Data Science Videos are Under construction
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