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Program overview
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Computational Mathematics for Data Science
Computational Mathematics for Data Science
Supercharge your company’s AI capabilities with our Computational Mathematics course. Learn how it enhances algorithm accuracy for smarter, faster AI systems. Join now!
Program Overview
Companies using advanced math techniques to optimize their AI algorithms have seen a ~40% boost in system performance. Computational Math has been known to sharpen data processing and fine-tune algorithms, transforming traditional AI systems into smarter, faster solutions that drive business growth.
Realizing its utility, our experts have designed the advanced Computational Mathematics training, catering to specific needs for AI and Data Science projects. Designed to empower your teams with the mathematical expertise they need, this course will unlock countless data-driven strategies and solutions to scale your business to greater heights.
The program is dynamic and engaging, offering 100% live training sessions where participants can interact and resolve their queries in real time. They will also participate in regular quizzes and work on hands-on projects, applying their skills to real-world applications as they learn.
Our course caters to people with different mathematical skills alike. Leaders will gain a better grasp of computational maths’ potential in existing workflows, while other team members will pick up the skills needed to tackle data-driven tasks efficiently. This combination can spark innovation and drive growth in your organization. Contact us to learn more about the same.
Personalised training curriculum
100% Live Sessions
Lifetime access to recordings and material
Hands-on labs and assignments included
Consulting Support
Delivered by industry experts
Why computational maths for your business?
- Deeper Data Insights: Employees and teams with computational expertise can analyze and interpret more complex datasets, allowing them to assist in better decision-making.
- Improved Predictive Modeling: Proficiency in computational maths enables your employees to design, build, and apply algorithms and predictive models, helping you forecast future trends accurately.
- More Effective Problem-Solving: Computational maths enhances problem-solving capabilities. Gaining expertise in this area will enable your employees to tackle data-related challenges with unique perspectives, allowing them to expedite data analysis.
- Hassle-Free AI/ML Integrations: Familiarity with computational mathematics allows your employees to understand and optimize complex AI/ML algorithms used to deal with diverse data types. This will simplify future integrations of AI/ML technologies in your existing workflows, ensuring seamless employee adoption and support.
Make Your Team Proficient
Training Objectives
- Develop an understanding of fundamental statistics for data science and analytics
- Master key principles of descriptive statistics and probability theory
- Learn and apply machine learning methods, including decision trees and decision forests.
- Gain insights into various probability distributions, such as normal and Poisson distributions
- Understand the fundamentals of hypothesis testing, including concepts like p-value, type I, and type II errors
- Get hands-on experience with logistic regression, multiple linear regression, and regression trees
Hands-on Experience with Tools
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Core Training Modules
- Quick Start
- An overview of the program, covering key mathematical concepts and tools for data science
- Introduction to Descriptive Statistics
- Overview of key concepts and goals
- The average value (Mean) in a dataset
- The middle value (Median) of ordered data
- The most frequent value (Mode)
- Guidelines on when to use mean, median, or mode
- Asymmetry (Skewness) in data distributions
- Data spread and variability using Range and Interquartile Range
- Population vs sample
- Data dispersion and consistency
- Impact of scaling & shifting on statistical measures
- Getting Equipped with Various Types of Distributions
- Overview of data distributions
- Normal Distribution
- Standardization using Z-Score
- Statistical Distributions
- Understanding Probability and Its Background Theory
- Fundamental probability concepts
- Rule of Addition for calculating combined probabilities
- Law of Multiplication to find the probability of multiple events
- Bayes Theorem and Expected Value
- Central Limit Theorem as a distribution of sample means
- Binomial Distribution
- Poisson Distribution for rare events
- Hypothesis Testing
- What is it and why is it done
- Significance Level and p Value with Type Error
- Population parameters - Confidence Interval and Margin of Error
- Hypothesis Test, T-Test, and T Distribution
- Law of Large Numbers
- Linear Regression and Advanced Regression
- Relationship modeling using Linear Regression
- Relationship strength with Correlation Coefficient
- Errors - Residual, MSE, and MAE
- Explained variance by Coefficient of Determination
- Model accuracy with RMS Error
- Machine Learning Algorithms
- Multiple Linear Regression for predicting outcomes
- How to avoid model overfitting in data analysis
- Polynomial Regression for nonlinear relationships
- Decision Tree for classification and regression tasks
- Regression Tree for predicting continuous outcomes
- Enhancing predictions with Random Forest ensemble
- Analysis of Variance
- Basics of ANOVA and assumption
- One-way ANOVA for means across groups
- F Distribution for variance ratios
- Two-way ANOVA and Sum of Squares
How does personalized training work?
01
Analyzing skill gap and assessing business requirements
02
Customising curriculum with core and additional modules to fit objectives
03
Supporting learning implementation with consulting
Who will benefit from this training?
- Data and Quantitative Analysts
- Cryptographers
- Software Developers
- Machine Learning Engineers
Is this training right for your team?
Frequently Asked Questions- Answered!
1. What are the pre-requisites for this training?
2. Will my team get any practical experience with this training?
3. What is your mode of delivery - online or on-sight?
4. Will trainees get certified?
5. What do we do if we need further support after the training?
Upskill My Team
- Personalised training curriculum
- 100% Live Sessions
- Lifetime access to recordings and material
- Hands-on labs and assignments included
- Consulting Support
- Delivered by industry experts
Accelerate Business Returns with In-Demand Technology and High-Performing Teams
Discover the power of digital transformation with train-to-deliver programs from Uptut's expert trainers and consultants trusted by 50,000+ professionals across the world's leading tech innovators.
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