The demand for data science is increasing day by day. Therefore, industries are looking for the expert data scientist. The [course_title] course teaches various tools and techniques of data science. You will learn various applications with the involvement of real-life practitioners.
Shortly, the course covers the Descriptive, Predictive and Prescriptive Analytics a practitioner needs to know about data science.
This course does not involve any written exams. Students need to answer 5 assignment questions to complete the course, the answers will be in the form of written work in pdf or word. Students can write the answers in their own time. Each answer needs to be 200 words (1 Page). Once the answers are submitted, the tutor will check and assess the work.
Edukite courses are free to study. To successfully complete a course you must submit all the assignment of the course as part of the assessment. Upon successful completion of a course, you can choose to make your achievement formal by obtaining your Certificate at a cost of £49.
Having an Official Edukite Certification is a great way to celebrate and share your success. You can:
- Add the certificate to your CV or resume and brighten up your career
- Show it to prove your success
Course Credit: NPTEL
|Lecture 01. Introduction. Prof. Deepu Philip||00:43:00|
|Lecture 02. Analytics for Decision Making Support. Prof. Deepu Philip||00:51:00|
|Lecture 03. Decision Needs and Analytics. Prof Deepu Philip||00:44:00|
|Lecture 04. Systems, Models and Modeling Process. Prof. Deepu Philip||00:42:00|
|Lecture 05. Types of Models. Prof. Deepu Philip||00:48:00|
|Lecture 06. Data and it types. Prof Deepu Philip||00:49:00|
|Lecture 07. Overview of Probability. Prof. Deepu Philip||00:47:00|
|Lecture 08: Statistics and Analytics_Prof. Deepu Philip||00:37:00|
|Lecture 09: Descriptive Statistics – Graphical Tools_Prof Deepu Philip||00:32:00|
|Lecture 10: Frequency Distribution & Histogram_Prof Deepu Philip||00:53:00|
|Lecture 11: Stem and Leaf Plot_Prof. Deepu Philip||00:37:00|
|Lecture 12: Box Plots_Prof. Deepu Philip||00:45:00|
|Lecture 13: Business Intelligence & Analytics_Prof. Deepu Philip||00:39:00|
|Lecture 14: Normal Distribution_Prof. Deepu Philip||00:30:00|
|Lecture 15: Sampling_Dr. Amandeep Singh||00:41:00|
|Lecture 16: Sampling Techniques_Dr. Amandeep SIngh||00:41:00|
|Lecture 17: Hypothesis Testing_Mr. Sanjeev Newar||00:53:00|
|Lecture 18: Hypothesis Testing continued_Mr. Sanjeev Newar||00:46:00|
|Lecture 19: Machine Learning_Mr. Sanjeev Newar||00:56:00|
|Lecture 20: Correlation_Dr. Amandeep Singh||00:23:00|
|Lecture 21: Correlation continued_Dr. Amandeep Singh||00:40:00|
|Lecture 22: Regression_Dr. Amandeep Singh||00:40:00|
|Lec 23 ANOVA_Part 1_Dr. Amandeep Singh||00:42:00|
|Lec 24 ANOVA_Part 2_Dr. Amandeep Singh||01:11:00|
|Lec 25 Machine Learning Part2_Sanjeev Newar||00:55:00|
|Lecture 26: Machine Learning Part 3_Mr. Sanjeev Newar||00:35:00|
|Lecture 27: Machine Learning Part 4_Mr. Sanjeev Newar||00:57:00|
|Lecture 28: Machine Learning Part 5_Mr. Sanjeev Newar||00:45:00|
|Submit Your Assignment||00:00:00|
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