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The Comprehensive 3-in-1 Data Science Bundle
Course 01: Data Science and Machine Learning with R
DSML_Promo (3:44)
Data_Science_ML_Course_Intro1 (2:30)
What_is_data_science (9:47)
Machine_Learning_Overview1 (5:26)
Whos_this_course_is_for1 (2:57)
DL_and_ML_Marketplace1 (4:38)
Data_Science_and_ML_Job_opps (2:37)
Data_Science_Job_Roles1 (4:04)
Getting_Started (10:58)
Basics (6:24)
Files (11:08)
RStudio (6:58)
Tidyverse (5:19)
Resources (4:02)
Section_Introduction (30:03)
Basic_Types (8:46)
Vectors_Part_One (19:40)
Vectors_Part_Two (24:51)
Vectors_Missing_Values (15:35)
Vectors_Coercion (14:07)
Vectors_Naming (10:16)
Vectors_Misc (5:59)
Creating_Matrices (31:27)
Lists (31:41)
Introduction_to_Data_Frames (19:20)
Creating_Data_Frames (19:50)
Data_Frames_Helper_Functions (31:12)
Data_Frames_Tibbles (39:03)
Section_Introduction_Intermediate_R (46:31)
Relational_Operations (11:06)
Logical_Operators (7:04)
Conditoinal_Statements (11:20)
Loops (7:56)
Functions (14:19)
Packages (11:29)
Factors (28:14)
Dates_and_Times (30:10)
Functional_Programming (36:41)
Data_Import_or_Export (22:06)
Database (27:08)
Data_Manipulation_in_R_Section_Introduction (36:29)
Tidy_Data (10:53)
The_Pipe_Operator (14:50)
The_Filter_Verb (21:34)
The_Select_Verb (46:03)
The_Mutate_Verb (31:57)
The_Arrange_Verb (10:03)
The_Summarize_Verb (23:05)
Data_Pivoting (42:41)
JSON_Parsing (10:46)
String_Manipulation (32:38)
Web_Scraping (58:53)
Data_Visualization_in_R_Section_Introduction (17:13)
Getting_Started (15:37)
Aesthetics_Mappings (24:45)
Single_Variables_Plot (36:50)
Two_Varible_Plots (20:34)
Facets_Layering_and_Coordinate_System (17:56)
Styling_and_Saving (11:33)
Creating-Reports-with-R-Markdown (28:54)
Section-Introduction-With-R-Shiny (26:05)
A_Basic_App (31:18)
Other_Examples (34:05)
Intro_to_Machine_Learning_-_Part_1 (21:48)
Intro_to_Machine_Learning_-_Part_2 (46:45)
Introduction_to_Data_Preprocessing (27:03)
Data_Preprocessing (37:47)
LR_Section_Introduction (25:09)
Linear_Regression_A_Simple_Model (53:05)
Section_Introduction_EDA (25:03)
Hands on_Exploratory_Data_Analysis (62:57)
Linear_Regression_Real_Model_Section_Intro (32:04)
Linear_Regression_in_R_real_model (52:48)
Introduction_to_Logistic_Regression (37:48)
Logistic_Regression_in_R (39:37)
Starting_a_Career_in_Data_Science (2:54)
Data_Science_Resume (3:43)
Getting_Started_with_Freelancing (4:44)
Top_Freelancing_Websites (5:18)
Personal_Branding (5:27)
Importance_of_Website_and_Blog (3:42)
Networking_dos_and_donts (3:50)
Course 2: Python for Data Science and Machine Learning
Who_is_this_Course_for (2:43)
DS__ML_Marketplace (6:55)
Data_Science_Job_Opportunities (4:24)
Data_Science_Job_Roles (10:23)
What_is_a_Data_Scientist (17:00)
How_To_Get_a_Data_Science_Job (18:39)
Data_Science_Projects_Overview (11:52)
Why_We_Use_Python (3:14)
What_is_Data_Science (13:24)
What_is_Machine_Learning (14:22)
ML_Concepts___Algorithms (14:42)
Machine_Learning_vs_Deep_Learning (11:09)
What_is_Deep_Learning (9:44)
What_is_Python_Programming (6:03)
Why_Python_for_Data_Science (4:35)
What_is_Jupyter (3:54)
What_is_Colab (3:27)
Jupyter_Notebook (18:01)
Getting_Started_with_Colab (9:07)
Python_Variables_Booleans_and_None (11:48)
Python_Operators (25:26)
Python_Numbers_and_Booleans (7:47)
Python_Strings (13:12)
Python_Conditional_Statements (13:53)
Python_For_Loops_and_While_Loops (8:07)
Python_Lists (5:10)
More_About_Python_Lists (15:08)
Python_Tuples (11:25)
Python_Dictionaries (20:19)
Python_Sets (9:41)
Compound_Data_Types_and_When_to_use_each_Data_Type (12:58)
Functions (14:24)
Python_Object_Oriented_Programming (18:47)
Intro_to_Statistics (7:11)
Descriptive_Statistics (6:35)
Measure_of_Variability (12:19)
Measure_of_Variability_Continued (9:35)
Measures_of_Variable_Relationship (7:37)
Inferential_Statistics (15:18)
Measures_of_Asymmetry (1:57)
Sampling_Distribution (7:34)
What_Exactly_Probability (3:44)
Expected_Values (2:38)
Relative_Frequency (5:15)
Hypothesis_Testing_Overview (9:09)
NumPy_Array_Data_Types (12:58)
NumPy_Arrays (8:22)
NumPy_Array_Basics (11:36)
NumPy_Array_Indexing (9:10)
NumPy_Array_Computations (5:53)
Broadcasting (4:32)
Intro_to_Pandas (15:52)
Intro_to_Panda_Continued (18:05)
Data_Visualization_Overview (24:49)
Different_Data_Visualization_Libraries_in_Python (12:48)
Python_Data_Visualization_Implementation (8:27)
Intro_to_ML (26:03)
Exploratory_Data_Analysis (13:06)
Feature_Scaling (7:41)
Data_Cleaning (7:43)
Feature_Engineering (6:11)
Linear_Regression_Intro (8:17)
Gradient_Descent (5:59)
Linear_Regression__Correlation_Methods (26:33)
Linear_Regression_Implemenation (5:06)
Logistic_Regression (3:22)
KNN_Overview (3:01)
Parametic_vs_Non-Parametic_Models (3:28)
EDA_on_Iris_Dataset (22:08)
KNN__Intuition (2:16)
Implement_the_KNN_algorithm_from_scratch (11:45)
Compare_the_Reuslt_with_Sklearn_Library (3:47)
KNN_Hyperparameter_tuning_using_the_cross-validation (10:47)
The_decision_boundary_visualization (4:55)
KNN_-_Manhattan_vs_Euclidean_Distance (11:21)
KNN_Scaling_in_KNN (6:01)
Curse_of_dimensionality (8:09)
KNN_use_cases (3:32)
KNN_pros_and_cons (5:32)
Decision_Trees_Section_Overview (4:11)
EDA_on_Adult_Dataset (16:53)
What_is_Entropy_and_Information_Gain (21:50)
The_Decision_Tree_ID3_algorithm_from_scratch_Part_1 (11:33)
The_Decision_Tree_ID3_algorithm_from_scratch_Part_2 (7:35)
The_Decision_Tree_ID3_algorithm_from_scratch_Part_3 (4:07)
ID3_-_Putting_Everything_Together (21:23)
Evaluating_our_ID3_implementation (16:51)
Compare_with_Sklearn_implementation (8:52)
Visualizing_the_Tree (10:15)
Plot_the_features_importance (5:51)
Decision_Trees_Hyper-parameters (11:39)
Pruning (17:11)
Optional_Gain_Ration (2:49)
Decision_Trees_Pros_and_Cons (7:31)
Project_Predict_whether_income_exceeds_50Kyr_-_Overview (2:33)
Ensemble_Learning_Section_Overview (3:46)
What_is_Ensemble_Learning (13:06)
What_is_Bootstrap_Sampling (8:25)
What_is_Bagging (5:20)
Out-of-Bag_Error (7:47)
Implementing_Random_Forests_from_scratch_Part_1 (22:34)
Implementing_Random_Forests_from_scratch_Part_2 (1:23)
Compare_with_sklearn_implementation (3:41)
Random_Forests_Hyper-Parameters (4:23)
Random_Forests_Pros_and_Cons (5:25)
What_is_Boosting (4:41)
AdaBoost_Part_1 (4:10)
AdaBoost_Part_2 (14:33)
SVM_-_Outline (5:16)
SVM_-_SVM_intuition (11:39)
SVM_-_Hard_vs_Soft_Margin (13:25)
SVM_-_C_HP (4:17)
SVM_-_Kernel_Trick (12:18)
SVM_-_Kernel_Types (18:13)
SVM_-_Linear_Dataset (13:35)
SVM_-_Non-Linear_Dataset (12:51)
SVM_with_Regression (5:51)
SVM_-_Project_Overview (4:26)
Unsupervised_Machine_Learning_Intro (20:22)
Representation_of_Clusters (20:49)
Data_Standardization (19:05)
PCA_-_Section_Overview (5:12)
What_is_PCA (9:37)
PCA_-_Drawbacks (3:31)
PCA_-_Algorithm_Steps (13:12)
PCA_-_Cov_vs_SVD (4:58)
PCA_-_Main_Applications (2:50)
PCA_-_Image_Compression_Scratch (27:00)
PCA_-_Data_Preprocessing_Scratch (14:31)
PCA_-_BiPlot (17:27)
PCA_-_Feature_Scaling_and_Screeplot (9:29)
PCA_-_Supervised_vs_unsupervised (4:55)
PCA_-_Visualization (7:31)
Creating_a_Data_Science_Resume (6:45)
Data_Science_Cover_Letter (3:33)
How_To_Contact_Recruiters (4:20)
Getting_Started_with_Freelancing (4:13)
Top_Freelance_Websites (5:35)
Personal_Branding (4:02)
Networking_Do_s_and_Don_ts (3:45)
Course 3: Ethical Hacking from Scratch
Course Promo (4:06)
Course_Overview (8:23)
About_Your_Instructors (2:31)
Section_Overview (3:20)
Current_Cybersecurity_Market (8:39)
The_3_Types_of_Hackers (4:51)
The_4_Elements_of_Security (4:06)
Ethical_Hacking_Terminology (3:45)
Common_Methods_of_Hacking (7:52)
Cyber_Security___Ethical_Hacking_Overview (2:31)
Ethical_Hacking_vs_Pentration_Testing (5:57)
Jobs_Opportunities_in_Cybersecurity (1:26)
Who_s_This_Course_For (1:15)
Networking_Section_Overview (11:57)
How_Data_Travels_Across_The_Internet (1:40)
Understanding_Ports_and_Protocols (8:23)
Public_Private_IP_s_Overview (2:14)
What_Are_Subnets (2:58)
The_Average_Network_vs_Remote_Based (5:33)
Hacking_Lab_Section_Overview (8:43)
Understanding_Virtual_Machines (3:22)
Setup_Your_Kali_Linux_Machine (9:33)
VN_Setup_Testing_Vulnerable_Systems (23:09)
LinuxPythonBashPowershell_Basics_Overview (5:38)
Linux_Basics (10:34)
Working_With_Directories___Moving_Files (2:46)
Installing_Updating_App_Files (2:03)
Linux_Text_Editors (4:29)
Searching_For_Files (2:17)
Bash_Scripting (9:02)
Python_Basics (10:38)
Remaining_Anonymous_Section_Overview (6:02)
TOR_Browser_Overview (5:31)
Anonsurf_Overview (3:16)
Changing_Mac_Addresses (2:43)
Using_a_Virtual_Private_Network___Server_(VPN_VPS) (4:20)
WiFi_Hacking_Section_Overview (5:39)
Wifi_Hacking_System_Setup (9:28)
WEP_Hacking_Attack_1 (8:31)
WEP_Hacking_Attack_2 (4:26)
WPA_WPA2_Hacking (10:20)
Reconnaissance_Section_Overview (3:58)
Passive_Active_Recon (1:12)
Recon-ng_Overview (14:51)
Whois_Enum (1:59)
DNS_Enumeration_Overview (2:07)
Netcraft_DNS_Information (2:31)
Google_Hacking_Overview (4:48)
Shodan.io_Overview (2:12)
Securityheaders.com_(Analyze_HTTPS_Headers_of_website) (1:45)
Ssllabs.comssltest_(Look_for_SSL_issues_on_website) (2:05)
Pastebin.com_(Sensitive_Information) (0:58)
NMAP_Port_Scanning_(Discover_open_ports_OS_Services (15:06)
Netcat_Overview_SMB_NFS_Enumeration (14:07)
Nikto_Sparta_Web_Application_Scanner (5:30)
SMPT_Enumeration__Nessus_Openvas_Scanners (4:30)
Launching_Attacks_Overview (10:18)
Analyzing_Information_Gathered (3:30)
Taking_Advantage_of_Telenet (6:01)
Searching_Understanding_Exploits (5:46)
Copy_Exploits_From_Searchsploit (2:51)
Understanding_Exploits (4:25)
Launching_Exploits (24:27)
Brute_Force_Attacks (6:53)
How_To_Crack_Passwords (4:13)
ARP_Spoofing_Overview (21:27)
Introduction_To_Cryptography (13:30)
Post_Exploitation_Section_Overview (3:07)
Privledge_Escalation (29:00)
Transferring_Files_Within_Victim_Creating_Custom_Malware_Evading_AV (27:23)
Installing_a_Keylogger (2:33)
Installing_a_Backdoor (6:30)
Website_Web_App_Hacking_Overview (6:08)
Web_Application_Scanning (7:51)
Directory_Buster_Hacking_Tool (2:49)
Nikto_Web_App_Hacking_Tool (3:27)
SQLmap_and_SQL_Ninja_Overview (0:46)
How_To_Execute_Brute_Force_Attacks (13:20)
Using_Command_Injection (3:21)
Malicious_File_Uploads (10:27)
Local_Remote_File_Inclusion (10:12)
SQL_Injection (18:32)
Using_Cross_Site_Forgery (10:58)
Cross_Site_Scripting_Overview (12:25)
Mobile_Phone_Hacking_Section_Overview (10:31)
Mobile_Attack_Vectors (1:57)
Mobile_Hacking_with_URL_s (2:03)
Jail_Breaking_and_Rooting_Considerations (0:55)
Privacy_Issues_(Geo_Location) (0:54)
Mobile_Phone_Data_Security (2:29)
Getting_Your_Name_Out_There_Section_Overview (2:09)
Building_A_Brand (9:13)
Personal_Branding (13:18)
Setup_Your_Website_and_Blog (11:26)
Writing_a_Book (9:52)
Starting_a_Podcast (8:14)
Networking_Overview (6:21)
Making_Money_Section_Overview (1:50)
Bug_Bounty_Programs (4:22)
How_To_Start_Freelancing (10:44)
How_To_Start_Client_Consulting (9:07)
Potential_Salary_Cybersecurity_Roadmap (10:26)
Book_Recomendations (2:32)
Places_to_Practice_Hacking_for_Free (3:14)
Why_Python_for_Data_Science
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