STATISTICS FOR DATA SCIENCE

The “Statistics for Data Science” course ensures that you learn practical implications of the statistical tools and excel in all of its concepts. Data Science is the extraction of knowledge from data, using concepts from mathematics, statistics, machine learning, computer programing. Data Science is one of the most happening fields in business today, creating a higher number of career opportunities. The certifications from DataMites are IABAC (International Association of Business and Analytics Certification) accredited which is a global certification. Statistics is used to process complex problems in the real-world so that Data Scientist and Analysts can derive meaningful changes in data by performing mathematical operations. This course also offers case studies for a better understanding and real-time experience. After completing the course, you’ll be joining all the high-end data scientists and decision-makers who are successfully shining in this career by using Minitab to analyze and visualize the business data.

DataMites offers training on weekends as well as weekdays which has different modes of training which could be chosen by the trainees to opt for,

  1. Classroom Training
  2. Online Live Virtual Training
  3. e-Learning

STATISTICS FOR DATA SCIENCE Training Cost

Live Virtual

340
159

  • IBM® & IABAC® Certification
  • 6-Month | 400 Learning Hours
  • 120-Hour Live Online Training
  • 20 Capstone & 1 Client Project
  • 365 Days Flexi Pass + Cloud Lab
  • Internship + Job Assistance

Self Learning

210
99

  • IBM® & IABAC® Certification
  • 365 Days Access
  • 20 Capstone & 1 Client Project
  • Internship +Job Assistance

Classroom

 

  • IBM® & IABAC® Certification
  • 6-Month | 400 Learning Hours
  • 64-Hour Classroom Sessions
  • 20 Capstone & 1 Client Project
  • Cloud Lab Access
  • Internship + Cloud Lab Access

ONLINE TRAINING SCHEDULES

Why Datamites

Why DataMites Infographic

Description

Statistics is one of the core disciplines of Data Science. Statistics is a vast field of study and Data Science requires only certain knowledge areas from Statistics such as data harnessing from various sources, understanding types of data and mathematical operations than can be performed on it, exploratory data analysis, measures of central tendencies and variability, hypothesis testing etc. As Data Science is about deriving insights from Data, Statistics becomes an important knowledge area.

Statistics as a field is vast and requires significant time and effort to gain practitioner level knowledge. This course is specifically designed to impart required statistics knowledge for data science practitioners. The syllabus of the course is in line with the international curriculum including knowledge areas of statistics that are quintessential for data science.

Statistics for the Data Science course take a practical approach by applying statistics concepts through case studies in the python platform, thereby enabling the candidates to learn essential statistics in the shortest and efficient way.

  • Understand Statistics as a field of study in broad areas of descriptive statistics and inferential statistics.
  • Gain knowledge in various data harnessing methods and statistical data analysis methods.
  • Apply hypothesis testing and several statistical techniques on data.
  • Solve case studies through the practical application of statistical methods in python with packages Scipy and Numpy.
  • Statistics is an essential skill in the field of Data Science. This course enables data science aspirants to gain statistics skills in the most effective way.
  • The course also takes a practical approach, thereby the candidates learn to apply these techniques for any data problems in various different areas.
  • Business Analytics practitioners improve their analytics works through statistical methods.
  • Data Engineers and related professionals enhance their statistics knowledge.
  • Managers, who require making decisions based on data.
  • Anyone aspiring to become a Data Science professional.
  • Research students to gain essential statistics skills.
  • There are no hard prerequisites for this course as it doesn't assume any prior knowledge.
  • Basic mathematics skills are recommended. 
  • Basic programming skills can be helpful when performing python case studies.

DataMites has provided training over 10,000 candidates in Data science courses across the globe and recognized as a leading institute for Data Science courses.

Statistics for Data Science course is designed as per the guidelines of the International Association of Business Analytics Certifications, IABAC.org a global board based in the Netherlands. 

IABAC® standards are aligned with the European Council and, thereby providing a strong basis for course coverage and quality of the training.

The trainers of DataMites™ are Ph.D. scholars with more than 15 years of Analytics industry experience. 

In short DataMites™ provides high-quality course training with practical case study approach, aligned with global standards.

Syllabus

  • Two areas of Statistics in Data Science
  • Applied statistics in business
  • Descriptive Statistics
  • Inferential Statistics
  • Statistics Terms and definitions
  • Type of Data
  • Quantitative vs Qualitative Data
  • Data Measurement Scales
  • Sampling Data, with and without replacement
  • Sampling Methods, Random vs Non-Random
  • Measurement on Samples
  • Random Sampling methods
  • Simple random, Stratified, Cluster, Systematic sampling.
  • Biased vs unbiased sampling
  • Sampling Error
  • Data Collection methods
  • Measures of Central Tendencies
  • Mean, Median and Mode
  • Data Variability : Range, Quartiles, Standard Deviation
  • Calculating Standard Deviation
  • Z-Score/Standard Score
  • Empirical Rule
  • Calculating Percentiles
  • Outliers
  • Distribtuions Introduction
  • Normal Distribution
  • Central Limit Theorem
  • Histogram - Normalization
  • Other Distributions: Poisson, Binomial et.,
  • Normality Testing
  • Skewness
  • Kurtosis
  • Measure of Distance
  • Euclidean , Manhattan and Minkowski Distance
  • Hypothesis Testing
  • Null Hypothesis, P-Value
  • Need for Hypothesis Testing in Business
  • Two tailed, Left tailed & Right tailed test
  • Hypothesis Testing Outcomes : Type I & II erros
  • Parametric vs Non-Parametric Testing
  • Parametric Tests ,  T - Tests : One sample, two sample, Paired
  • One Way ANOVA
  • Importance of Parametric Tests
  • Non Parametric Tests : Chi-Square, Mann-Whitney, Kruskal-Wallis etc.,
  • Which Test to Choose?
  • Ascerting accuracy of Data
  • Introduction to Regression
  • Type of Regression
  • Hands on of Regression with R and Python.
  • Correlation
  • Weak and Strong Correlation
  • Finding Correlation with R and Python

FAQ'S

DataMites™ provides flexible learning options from traditional classroom training, lastest virtual live classroom to distance course. Based on your location preference, you may have one or more learning options.

This course is perfectly aligned to the current industry requirements and gives exposure to all latest techniques and tools. The course curriculum is designed by specialists in this field and monitored and improved by industry practitioners on continual basis.

All certificates can be validated with your unique certification number at IABAC.org portal. You also get candidate login at exam.iabac.org, where you can find your test results and other relevant validation details.

The results of the exam would be reflected immediately when you take the test online at exam.iabac.org portal. The certificate issuance, as per IABAC™ terms, takes about 7-10 business days for e-certificate.

No, the examination fees is already included in the course fee and you would not be charged any extra.

Course fee needs to be paid in one payment as it is required to block your seat for the entire course as well as book the certification exams with IABAC™. In case, if you have any specific constraints, your relationship manager at DataMites™ shall assist you with part payment agreements.

DataMites™ has a dedicated Placement Assistance Team(PAT), who work with candidates on individual basis in assisting for right Data Science job.

You get 100% refund if you are not satisfied with the training but the exam cannot be refunded as we pay to accreditation bodies. If the refund is due to your availability concerns, you may need to talk to the relationship manager and will be sorted out on case to case basis.

DataMites™ provides loads of study materials, cheat sheets, data sets, videos so that you can learn and practice extensively. Along with study materials, you will get materials on job interviews, new letters with latest information on Data Science as well as job updates.

The DataMites Placement Assistance Team(PAT) facilitates the aspirants in taking all the necessary steps in starting their career in Data Science. Some of the services provided by PAT are: -

  • 1. Job connect
  • 2. Resume Building
  • 3. Mock interview with industry experts
  • 4. Interview questions

The DataMites Placement Assistance Team(PAT) conducts sessions on career mentoring for the aspirants with a view of helping them realize the purpose they have to serve when they step into the corporate world. The students are guided by industry experts about the various possibilities in the Data Science career, this will help the aspirants to draw a clear picture of the career options available. Also, they will be made knowledgeable about the various obstacles they are likely to face as a fresher in the field, and how they can tackle.

No, PAT does not promise a job, but it helps the aspirants to build the required potential needed in landing a career. The aspirants can capitalize on the acquired skills, in the long run, to a successful career in Data Science.

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