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Students will get the certificate upon completion of the course
A Glimpse from the previous batch
Why this course:
Artificial intelligence (AI) is wide-ranging branch of computer science concerned with building smart machines capable of performing tasks that typically require human intelligence. AI is an interdisciplinary science with multiple approaches, but advancements in machine learning and deep learning are creating a paradigm shift in virtually every sector of the tech industry. Machine learning feeds a computer data and uses statistical techniques to help it "learn" how to get progressively better at a task, without having been specifically programmed for that task, eliminating the need for millions of lines of written code
Software: Anaconda Navigator Latest (IDE) version
Why AI & Machine Learning with Skyy RIder?
Skyy Rider offeres best in class Machine Learning with Python Training in a complete live & hands-on pedagogy which makes a students industry ready. The python programming language is delivered by professionals who have worked in various program Industry.
⇒ This program can help in preparing a students for Higher study
⇒ Students can learn and start their own start-up in AI & Machine Learning
⇒ Students who are aspiring to be in Machine learning Job
COURSE CONTENT
1st Week
Python Environment Concepts
1. Jupyter Note Book – Spyder Overview
2. JYNB Working Environment
3. Structure of jpynb
4. Saving/Loading Notebook
5. Edit Cells /View Cells /Insert Cells
6. Keyboard Shortcuts /Magic Commands
7. Execute Cells /Kernel Cells /Widgets / Markdown
Core Python Programming
8. Elementary Programming with simple examples
9. Mathematical Functions, Strings, and Objects
10. Loops with programming
11. Functions & Class functions generation
12. Import functions & generate user define import functions
2nd Week
Advanced Python Programming
13. Data structures [List, Tuple, Set, Frozen set, and Dictionary]
14. Build in Functions & Lambda Functions
15. Packages, Modules
16. Math, OS, Random, Statistics, Sys, other Modules
17. Create UDM (User Defined Modules)
Data Analysis with
18. Numpy
19. Scipy
20. Pandas
21. Seaborn
22. Bokeh
3rd Week
Overview of Artificial Intelligence & Machine learning
23. Introduction to types of Machine Learning
24. Introductions to Supervised Learning
25. Introductions to Unsupervised Learning
26. Introduction to Reinforcement learning
27. Introductionsto ML with Pipelines – Automatic Workflows
28. Introductions to Improving Performance of ML Models
29. Performance Improvements with Algorithm Tuning_1
30. Performance Improvements with Algorithm Tuning_2
31. Introduction to types of Artificial Intelligence
32. Introductions to Reactive Machines
33. Introductions to Limited Memory
34. Introductions to Theory of Mind
35. Search Techniques.
36. Knowledge Representations
37. Neural networks and Deep learning.
38. Natural language processing
39. Fuzzy logic and its applications
40. Introductions to AI with Python – Speech Recognition
Types of Data Analysis
39 Descriptive Analyses
40 Exploratory Data Analysis
41. Predictive Analysis
44. Inferential Analysis
4th Week
Data Visualization with Matplotlib
45. Working with Pyplot
46. Lines, Bar, Pie, Scatter, Histogram, Box, Violin Plots
Algorithms Implementation
47. Introduction to Algorithm and how it is implement
48. Algorithm_1 Linear regressions.
49. Algorithm_2 logistic regressions.
50. Algorithm_3 Decision tree.
51. Algorithm_4 Support Vector Machine (SVM)
52. Algorithm_5 Naive Bayes)
53. Algorithm_6 KNN algorithm.
54. Algorithm_7 K-means
55. Algorithm_8 Random forest algorithms.
Industry Based Project &Machine learning and Artificial Intelligence libraries in python
56. My first project in AI & ML
57. Case study Industry Project and Implementation with analysis
→ Total 50 Seats Per batch
→ Students need to pay the course fees and fill the registration form to enroll themself.
→ Go to the enrolment section to register for the program.
→ After completion of all the processes, students will receive an intimation from our team regarding their batch details.
→ 10% OFF on course fees for 5 students enrolling together. Contact us for the Payment link.
FAQs:
→ Duration of class: Offline courses Upto 2:00 hours Daily after 6:00 PM IST.
→ Best For: Working Professionals in IT Sector, Building a great profile for Higher Study
→ LOR- Yes students can apply for LOR
→ Students or Professional: Both can join
→ Discount: Group enrolment discount available for a group of students of 5 or more.
→ Special batch Commencement: For a group of 40 students from the same college we can arrange a special batch as per their convenience.
→ Certificates: Participants will get a completion certificate from Gram Tarang (Partner of NSDC) & Skyy Rider
→ Project Certificate: Yes students will get a project certificate after the course
10% further discount for group registration available. Click below to get the discounted link.
To reach every student, we are constantly developing & expanding our business processes.
1: 3rd floor, Sreshta Marvel, Sy.No.136, Kondapur Main Road, Gachibowli, Hyderabad 500032
2: Awfis, 1st floor, SRB Towers, E-12, Infocity, Patia Bhubaneswar 751024
GRIET College, Nizampet Road, Bachupally, Kukatpally, Hyderabad- 500090
CUTM, Village Alluri Nagar, R.Sitapur, Jatni, Bhubaneswar, Odisha 761211
Government Polytechnic, Rail Vihar, Chandrasekharpur, Bhubaneswar, Odisha 751013
