Machine Learning Beginner to Advanced with Global Certification

 Online Class

316   Users Booked

$ 70

SYLLABUS

Total Sessions: 39 | Total Hours: 50 Hours

1. Introduction to Machine Learning(1 Session)
All the Basics, Data Science Modules and Application of Machine Learning and its tools
2. Introduction to Python and IDE(1 Session)
Different flavors and platforms, Install Anaconda, Python IDE: Spyder, Setting your work directory, The libraries that you should know, IPython and Python Notebook
3. Introduction to Python Programming and Data Type(1 Session)
Introduction to Python Programming, Python Handson, Data Type, Tuples and Dictionary, List and Set
4. Numpy Packages and its Handson(1 Session)
Numpy Package, Creating arrays, Indexing, Data Processing using Arrays and File Input & Output.
5. Pandas Packages and its Handson(1 Session)
Introduction to Pandas Packages, Pandas Packages Handson, Create the Data frame and List and Data frame and Set and OTS Hanson
6. Data Visualization using Matplotlib Packages(1 Session)
Introduction to Data Visualization, Handson Line Graph, Pie Chart, Bar Graph and Scatter Plot, Handson Exercise using Matplotlib
7. Descriptive Statistics using Pandas(1 Session)
Introduction to Descriptive statistics and central Tendency, Measure of Dispersion, Distribution of Shape and Outliers, Descriptive Statistics Handson
8. Hypothesis Testing and its Process(1 Session)
Introduction to Hypothesis, Hypothesis Formulation and Process, Errors in Hypothesis
9. Inferential Statistics using Scipy(1 Session)
Introduction to Inferential statistics, Non Parametric Test using Scipy, Non Parametric Test Handson, Parametric Test handsome using Scipy
SHOW MORE SESSIONS
10. Data Preparation Process and EDA(1 Session)
This part cover Data Preparation Process and Exploratory Data Analysis (EDA)
11. Measurement and Scaling(1 Session)
This part cover Data Analysis, Comparative Scaling Techniques and Non Comparative Scaling Techniques
12. Data Collection and Data Treatment(1 Session)
This part cover Data Collection Methods and Data Types and Data Source error and Data Treatment
13. Correlation and Application(1 Session)
Introduction to Correlation, Product Moment Correlation and Its Application, Correlation Using Hypothesis Test, Correlation Handson using scipy packages
14. Questionnaire Design Process(1 Session)
This part cover Questionnaire Design Process, Application on Questionnaire Design
15. Linear Regression and its Application(1 Session)
This part cover Linear Regression Introduction, Simple Regression using Hypothesis testing, Multiple Regression and its an Assumption, Simple and Multiple Regression Handson using Python codes
16. Probability and its Bayes Theorem(1 Session)
This part cover Probability Introduction and its Application, Bayes Theorem using Probability
17. Discrete Probability Distribution(1 Session)
Discrete Probability Distribution - Binomial and Poisson, Hyper geometric Distribution and its Application
18. Continuous Probability Distribution(1 Session)
This part cover Continuous Probability, Uniform, Normal and Exponential Distribution, Application of Continuous Probability Distribution
19. ANOVA - Analysis of Variance(1 Session)
This part cover ANOVA Using Hypothesis Testing, Handson using Python
20. ANCOVA - Analysis of Covariance(1 Session)
This part cover ANCOVA using Hypothesis Testing and Handson
21. Discrimiant Analysis(1 Session)
This part cover Discriminant Analysis and its Application and Handson using Python
22. Logistic Regression(1 Session)
Logistic Regressions Methods and Application and Handson using Sklearn Packages
23. Time Series(1 Session)
This part cover Components and Smoothing and Forecasting Methods and Handson
24. Factor Analysis(1 Session)
This part cover PCA and Rotation Method, Real Time Case Study and Hands on Using Sklearn
25. Cluster Analysis(1 Session)
This part Hierarchical Clustering, Non Hierarchical Clustering and Handson Using Cluster Analysis
26. Data Architecture(1 Session)
This part cover Data Architecture and Data Warehousing and Multidimensional Model
27. Association Rule - Apriori Algorithm(1 Session)
This part Apriori Algorithm, Market Basket Analysis and Handson using Apriori Algorithm
28. Artificial Neural Network(1 Session)
This part cover Single and Multi Layered Architecture, ANN With Real time Example
29. Decision Tree(1 Session)
Introduction and Implementation Logics and Handson using Sklearn Packages
30. Random Forest(1 Session)
Introduction and Implementation Logics and Handson using Sklearn Packages
31. Naive Bayes Classification(1 Session)
Naive Bayes - Introduction and Implementation Logics and Naive Bayes - Handson using Sklearn Packages
32. K Nearest Neighbor(1 Session)
KNN - Introduction and Implementation Logics and KNN - Handson using Sklearn Packages
33. Support Vector Machine(1 Session)
SVM - Introduction and Implementation Logics and SVM - Handson using Sklearn Packages
34. Experimental Deign(1 Session)
Basic Experimental Design and its Application and Complex Experimental Design and its Application
35. Image Processing(1 Session)
Image Processing and its application and Image Processing and its histogram features
36. Image Recognition(1 Session)
Image Recognition and its Application and Viola Jones Algorithm and its Application
37. Operational Analytics and its Case Study(1 Session)
Scope of the Project and Economic Industry Analysis, Company Analysis and its Competitor Analysis, Project Specific Analysis and Theoretical Framework, Limitations, Findings and Recommendation.
38. Finance Analytics and its Application(1 Session)
Credit Risk Analytics using Logistic Regression, Merger and Acquisitions Analysis using Financial Analytics, Financial Ratio Analysis using Analytics, Companys Financial Analytics
39. Machine Learning complete Recapsulation(1 Session)
Machine Learning - Statistics and Visualisation and Supervised and Unsupervised Algorithm
CLASS SUMMARY
The course is taken by Dinesh Babu a CBAP certified professional and a Senior Business Analyst. He undertakes Data Analysis Training for Indian as well as students overseas.During his teaching with spans over 8 years, his deep knowledge and expertise on the subject has won his several awards the most notable of which is the Best Data Science Teacher in Delhi- 2017.
This course gives an introduction into the field of business intelligence and business analytics-domains which extensively use data to take decisions. The course delves into statistics, quantitative analysis, exploratory predictive models, and fact-based management which are indispensable tools for any aspiring data scientist/analyst.
Following are the specialties of the program:
1. We have a live prime time questions support in the app itself with the tutor (https://play.google.com/store/apps/details?id=com.braingroom.user)
2. 20minute rule Quiz questions on topics learned in the interval of every twenty minutes
3. Weekly assignments and prereading / postreading content will be shared as project material
4. Curated course conducted with inputs from industry experts
5. Internship opportunities for students qualifying the final evaluation, We are partnering with several tech startups across India to give students real time work experience
6. Internship with various startups in India for individuals who clears Company's assessment
7. Tutor time Live Q & A Session with Tutor once a week
8. Online classes can be taken at any place and at any time as per the learner's convenience & availability
ABOUT CLASS
Course gives you a comprehensive understanding of Machine Learning right from basic to advanced levels. Even Students without basic understanding of Machine Learning can take up this course.
The Machine Learning course will cover the following topic such Introduction to Machine Learning, Numpy Packages and its Handson, Pandas Packages and its Handson, Data Preparation Process and EDA, Linear Regression and its Application, ANOVA - Analysis of Variance, ANCOVA - Analysis of Covariance, Time Series, Marketing Analytics and its Case Study, Finance Analytics and its Application etc.,
ABOUT ACADEMY
The Tutor:-
Dinesh Babu ,B.Tech,MBA,Ph.D with dual specialization in Finance and Operation. He completed Ph. D. in Data Analysis from BITS, Pilani. Currently,a Senior Business Analyst in a MNC.His zeal and passion for up-scaling youth has propelled him into teaching and the 8 years that followed has seen him get several awards and citations.
Braingroom Skill Centre:-
We are happy to host Mr. Dinesh Babu energetic tutor in our portal for conducting Machine Learning through Python. Currently under the elite FACEBOOK SheLeadsTech India mentorship program, Braingroom has built a name for itself being an education and learning platform where we have a wide offering of multilingual online and offline classes with the vision of upskilling India's youth. With 20000+ Online Leaners, 2000+ Classes in 55+ Categories and with an experience of having trained 30000+ students (Online + Offline) and expertise/Industry connects enabling 100s of Students Internships, Braingroom Skill centre stands tall among competition in the online learning space as the only complete online learning ecosystem in the country.
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